10 items tagged "data visualization"

  • ‘World Situation Room’ visualiseert wereldwijde impact coronavirus

    ‘World Situation Room’ visualiseert wereldwijde impact coronavirus

    Toucan Toco en CashStory hebben hun expertise ingezet om data over de coronacrisis door middel van datavisualisatie beter leesbaar en voor iedereen toegankelijk te maken. De applicatie World Situation Room toont nauwkeurige en relevante informatie over de impact van het Covid-19 virus op de wereldwijde gezondheid en economie in een interactief dashboard.

    World Situation Room visualiseert updates over de wereldwijde verspreiding van de Covid-19 pandemie, met onder andere het aantal bevestigde besmettingen en genezen verklaarde patiënten. Door deze gegevens in een interactief dashboard weer te geven worden trends inzichtelijk, net als een ranking van de verschillende landen waar besmettingen zijn vastgesteld. 

    Daarnaast toont het dashboard informatie over de wereldwijde economische impact van de coronacrisis, met data over aandelen, grondstoffen, valuta’s en algemene economische indicatoren.

    Gebruikers van het interactieve dashboard kunnen de informatie naar wens op globaal of nationaal niveau bekijken. 

    De applicatie is een bètaversie, er wordt gewerkt aan het toevoegen van onder andere rentetarieven, logistiek en supply chain updates en het tonen van financiële concessies verleend door regeringen ter ondersteuning van handel en industrie. 

    “In een tijd van ongekende onzekerheid en volatiliteit, is het onze missie om één bron te bieden van nauwkeurige en up-to-date informatie over gezondheids- en economische ontwikkelingen,” aldus Baptiste Jourdan, oprichter van Toucan Toco. 

    Bron: Toucan Toco

  • 10 dashboarding best practices to get the most out of analytics

    10 dashboarding best practices to get the most out of analytics

    Dashboards are the control centers for your analytics, putting vital metrics at your fingertips and creating a visual representation of data mining. But building them can be difficult and sometimes confusing. Not all dashboards are created equal, and it’s important to understand the key components that will optimize your expertise for success, impact and peak performance. Design and simplicity play vital roles, as does a mindful focus on key performance indicators (KPIs) from the very first moment. 

    If you’re building a dashboard and looking for ways to optimize it, keep these 10 best practices in mind:

    1. Consider a dashboard a blank canvas for your own work of art

    An artist staring at a blank canvas and a tub of paint understands that these are merely tools for the end game: a work of art. When you design a dashboard, adopt a similar perspective by maintaining a mental target of your desired deliverables before you begin. What do you as a user want to show management or another audience via this dashboard, and what types of actions do you want to compel them to take when they look at it?

    A dashboard can serve as the bridge between data and action, but to build it properly, you need to understand who will be looking at the dashboard and what its metrics will compel them to do. If you want to create a dashboard to look at the top spend and expenses in your organization, the goal that you should have in mind at all points of creation is showing management how much they spend in each specific timeframe. And let it literally be a canvas: I always recommend that you draft your dashboard’s entire layout on a piece of paper first before moving to the real thing, which will help you project what you see in your mind. For some people, this is a really helpful first step before building. 

    2. Focus on data to insight and decision

    Now that you understand your dashboard is a work of art, let’s add another layer: your dashboard is also a critical tool helping your management and your audience to take decisive action for your company. When selecting metrics, keep this in mind and it will guide your design process and overall selection. 

    3. Give your dashboard a title

    Just like PowerPoint slides, a dashboard also needs a clear message. When people open your dashboard, you want to make sure that the first thing that meets their eye is the name or title of your dashboard. This is their first impression of your entire analytics journey, and it should be clear and concise. 

    And don’t forget that first impressions can happen across a variety of devices. A lot of your audience will be looking at your dashboard on a mobile device rather than a desktop, so make sure you’ve optimized the viewing experience for both. Whether viewed on an iPhone, a tablet, a laptop or a desktop computer, anyone who opens your dashboard should know immediately what that the title is and what the information they’re viewing is all about.

    4. Include data visualization context

    Each data visualization on your dashboard needs a title, description, point of view, and date and time stamp to provide viewers with context and understanding. This information presents a guide and a model for further KPIs. 

    5. Ensure load speed is close to a second

    Information is useless if it can’t be understood. In the case of a dashboard, less is more and simplicity is key. This will also help performance.

    Ideally, a dashboard should open in 1-2 seconds. A good rule of thumb is that it opens in less than one minute. If your dashboard takes more than one minute to load, there might be a problem on the data modelling side. One easy way to boost query speed is to transfer the underlying database to the Autonomous Data Warehouse. 

    6. Keep maintenance in mind

    While creating your dashboard, make sure that you know exactly how long it will take to maintain it for future updates. Data quality is just as important as the data visualization itself. If a dashboard does not have 100% accurate data, you can’t deliver facts and management can’t make fact based decisions. So, after you acquire the data and create your work of art, be sure you have a plan for updating it, including refreshing the data, and transforming it and displaying it, for the long haul. 

    7. Don’t forget about logos and branding

    There was a time, several years ago, when standards for dashboard design were low. Those days are past, and it’s important to use all of the options in the toolbox. Remember that logos, branding, and company communication need to be clearly and consistently presented. If your dashboard is being communicated inside of your organization, it’s always good for people to be able to identify it right away. Use your company logo and keep it prominent, and also keep in mind the basic color palette and design philosophy to which your branding is aligned.  

    8. With KPIs, less is more

    It’s very tempting to include 1,000 different pieces of information on the dashboard, with 10 or 20 different filters. No one wants to leave out critical information. But remember that less is more. Too many KPIs create a classic case of “too much of a good thing,” forcing the user into information overload and clogging up the dashboard so that data cannot be properly visualized. Overwhelming people with information can make them question your dashboard and the data, reducing your impact.

    Instead, set five or six KPIs as your data visualization maximum. This doesn’t mean that you need to leave deeper information on the cutting room floor; it simply means that you should allow an option to drill down into these KPIs via sub KPIs.  

    9. Don’t forget about the footer

    Dashboards need information context, which can be featured in the footer. The footer is the critical spot where you share the name of the dashboard’s author, and if appropriate, the data sources used. 

    The footer is also your tool spot for more context on viewer information. Is the dashboard restricted or confidential? Keep that information in the footer. It’s also the spot to put contact information like an email or phone number so that if any user has a question about the dashboard, they can reach out for clarification. These more than nice things to do, they are thoughtful touches that make your dashboard more usable, which your audience will appreciate. 

    10. Filter your filter use

    Some people love filters. But filters need to be used sparingly, and with care. The more you offer filters to slice and dice data via categories like region, the more you open yourself up to the risk of the dashboard not being current or presenting incorrect data. Above all, make sure that your dashboard is clear and the data is understandable with all filters removed. 

    Putting It All Together

    Here are the key takeaways:

    • When you’re building a dashboard, take time before you begin to focus on your goals. Think to yourself, “When someone looks at my dashboard, what do I want them to see and what actions do I want them to take?”
    • When you’re working, focus on delivering data that leads to insights and decisions.
    • Keep simplicity and clarity in mind by providing a title, context, logos, branding, and a footer.
    • Ensure that your load speed is close to a second and that your dashboard is easy to maintain.
    • Be sure to choose five or six KPIs, and use filters sparingly. 

    Your dashboard doesn’t have to say everything and it doesn’t have to include everything. It’s a guide. Trust your judgment, remember less is more, and you’ll be on the right track before you even begin.

    Author: Benjamin Arnulf

    Source: Oracle

  • 13 Tips & Techniques to use when Visualizing Data

    13 Tips & Techniques to use when Visualizing Data

    “By visualizing information, we turn it into a landscape that you can explore with your eyes. A sort of information map. And when you’re lost in information, an information map is kind of useful.” – David McCandless

    Did you know? 90% of the information transmitted to the brain is visual.

    Concerning professional growth, development, and evolution, using data-driven insights to formulate actionable strategies and implement valuable initiatives is essential. Digital data not only provides astute insights into critical elements of your business but if presented in an inspiring, digestible, and logical format, it can tell a tale that everyone within the organization can get behind.

    Data visualization methods refer to the creation of graphical representations of information. Visualization plays an important part in data analytics and helps interpret big data in a real-time structure by utilizing complex sets of numerical or factual figures.

    With the seemingly infinite streams of data readily available to today's businesses across industries, the challenge lies in data interpretation, which is the most valuable insight into the individual organization as well as its aims, goals, and long-term objectives.

    That's where data visualization comes in.

    Due to the way the human brain processes information, presenting insights in charts or graphs to visualize significant amounts of complex data is more accessible than relying on spreadsheets or reports.

    Visualizations offer a swift, intuitive, and simpler way of conveying critical concepts universally – and it's possible to experiment with different scenarios by making tiny adjustments.

    Recent studies discovered that the use of visualizations in data analytics could shorten business meetings by 24%. Moreover, a business intelligence strategy with visualization capabilities boasts a ROI of $13.01 back on every dollar spent.

    Therefore, the visualization of data is critical to the sustained success of your business and to help you yield the most possible value from this tried and tested means of analyzing and presenting vital information. To keep putting its value into perspective, let’s start by listing a few of the benefits businesses can reap from efficient visuals. 

    Benefits Of Data Visualization Skills & Techniques

    As we just mentioned in the introduction, using visuals to boost your analytical strategy can significantly improve your company’s return on investment as well as set it apart from competitors by involving every single employee and team member in the analysis process. This is possible thanks to the user-friendly approach of modern online data analysis tools that allow an average user, without the need for any technical knowledge, to use data in the shape of interactive graphs and charts in their decisions making process. Let’s look at some of the benefits data visualization skills can provide to an organization. 

    • Boosts engagement: Generating reports has been a tedious and time-consuming task since businesses and analytics came together. Not only are static reports full of numbers and text quickly outdated, but they are also harder to understand for non-technical users. How can you get your employees to be motivated and work towards company goals when they might not even understand them? Data visualizations put together in intuitive dashboards can make the analysis process more dynamic and understandable while keeping the audience engaged.  
    • Makes data accessible: Following up on the accessibility point, imagine you are an employee that has never worked with data before, trying to extract relevant conclusions from a bunch of numbers on a spreadsheet can become an unbearable task. Data visualizations relieve them from that burden by providing easy access to relevant performance insights. By looking at well-made graphs and charts, employees can find improvement opportunities in real-time and apply them to their strategies. For instance, your marketing team can monitor the development of their campaigns and easily understand at a glance if something is not going as expected or if they exceeded their initial expectations. 
    • They save time: No matter the business size, it is very likely that you are working with raw data coming from various sources. Working with this raw data as it is can present many challenges, one of them being the amount of time that it takes to analyze and extract conclusions from it. A time that could be spent on other important organizational or operational tasks. With the right data visualization tools and techniques, this is not an issue, as you can quickly visualize important performance indicators in stunning charts within seconds.  Like this, you can build a complete story, find relationships, make comparisons, and navigate through the data to find hidden insights that might otherwise remain untapped. 

    13 Tips & Techniques to use when Visualizing Data

    Now that you have a better understanding of how visuals can boost your relationship with data, it is time to go through our top techniques, methods, and skills needed to extract the maximum value out of this analytical practice. Here are 13 essential data visualization techniques you should know.

    1. Know Your Audience

    This is one of the most overlooked yet vital concepts around.

    In the grand scheme of things, the World Wide Web and Information Technology as a concept are in their infancy - and data visualization is an even younger branch of digital evolution.

    That said, some of the most accomplished entrepreneurs and executives find it difficult to digest more than a pie chart, bar chart, or a neatly presented visual, nor do they have the time to delve deep into data. Therefore, ensuring that your content is both inspiring and tailored to your audience is one of the most essential data visualization techniques imaginable.

    Some stakeholders within your organization or clients and partners will be happy with a simple pie chart, but others will be looking to you to delve deeper into the insights you’ve gathered. For maximum impact and success, you should always conduct research about those you’re presenting to prior to a meeting, and collate your report to ensure your visuals and level of detail meet their needs exactly.

    2. Set Your Goals

    Like any business-based pursuit, from brand storytelling right through to digital selling and beyond - with the visualization of your data, your efforts are only as effective as the strategy behind them.

    To structure your visualization efforts, create a logical narrative and drill down into the insights that matter the most. It’s important to set a clear-cut set of aims, objectives, and goals prior to building your management reports, graphs, charts, and additional visuals.

    By establishing your aims for a specific campaign or pursuit, you should sit down in a collaborative environment with others invested in the project and establish your ultimate aims in addition to the kind of data that will help you achieve them.

    One of the most effective ways to guide your efforts is by using a predetermined set of relevant KPIs for your project, campaigns, or ongoing commercial efforts and using these insights to craft your visualizations.

    3. Choose The Right Chart Type

    One of the most effective data visualization methods on our list; is to succeed in presenting your data effectively, you must select the right charts for your specific project, audience, and purpose.

    For instance, if you are demonstrating a change over a set of time periods with more than a small handful of insights, a line graph is an effective means of visualization. Moreover, lines make it simple to plot multiple series together.

    4. Take Advantage Of Color Theory

    The most straightforward of our selected data visualization techniques - selecting the right color scheme for your presentational assets will help enhance your efforts significantly.

    The principles of color theory will have a notable impact on the overall success of your visualization model. That said, you should always try to keep your color scheme consistent throughout your data visualizations, using clear contrasts to distinguish between elements (e.g. positive trends in green and negative trends in red).

    As a guide, people, on the whole, use red, green, blue, and yellow as they can be recognized and deciphered with ease.

    5. Handle Your Big Data

    With an overwhelming level of data and insights available in today’s digital world - with roughly 1.7 megabytes of data to be generated per second for every human being on the planet by the year 2020 - handling, interpreting, and presenting this rich wealth of insight does prove to be a real challenge.

    To help you handle your big data and break it down for the most focused, logical, and digestible visualizations possible, here are some essential tips:

    • Discover which data is available to you and your organization, decide which is the most valuable, and label each branch of information clearly to make it easy to separate, analyze, and decipher.
    • Ensure that all of your colleagues, staff, and team members understand where your data comes from and how to access it to ensure the smooth handling of insights across departments.
    • Keep your data protected and your data handling systems simple, digestible, and updated to make the visualization process as straightforward and intuitive as humanly possible.
    • Ensure that you use business dashboards that present your most valuable insights in one easy-to-access, interactive space - accelerating the visualization process while also squeezing the maximum value from your information.

    6. Use Ordering, Layout, And Hierarchy To Prioritize

    Following on our previous point, once you’ve categorized your data and broken it down to the branches of information that you deem to be most valuable to your organization, you should dig deeper, creating a clearly labeled hierarchy of your data, prioritizing it by using a system that suits you (color-coded, numeric, etc.) while assigning each data set a visualization model or chart type that will showcase it to the best of its ability.

    Of course, your hierarchy, ordering, and layout will be in a state of constant evolution but by putting a system in place, you will make your visualization efforts speedier, simpler, and more successful.

    7. Utilize Word Clouds And Network Diagrams

    To handle semi-structured or decidedly unstructured sets of data efficiently, you should consult the services of network diagrams or cloud words.

    A network diagram is often utilized to draw a graphical chart of a network. This style of layout is useful for network engineers, designers, and data analysts while compiling comprehensive network documentation.

    Akin to network diagrams, word clouds offer a digestible means of presenting complex sets of unstructured information. But, as opposed to graphical assets, a word cloud is an image developed with words used for particular text or subject, in which the size of each word indicates its frequency or importance within the context of the information.

    8. Use Text Carefully 

    So far, we’ve made it abundantly clear that the human brain processes visuals better than text. However, that doesn’t mean you should exclude text altogether. When building efficient graphics with your data, the use of text plays a fundamental role in making the graphs understandable for the audience. That said, it should be used carefully and with a clear purpose. 

    The most common text elements you can find in data visualizations are often captions, labels, legends, or tooltips just to name a few. Let’s look at each of them in a bit more detail. 

    • Captions: The caption occupies the top place in a graph or chart and it tells the user what he or she should look for in that visual. When it comes to captions you should always avoid verbosity. Keep them short and concise and always add the units of measurement. 
    • Labels: Labels describe a value associated with a specific data point in the chart. Here it is important to keep them short, as too long labels can crowd the visual and make it hard to understand. 
    • Legends: A legend is a side section of a chart and it shows and it gives a brief description to help users understand the data being displayed. For example, what each color means. A good practice when it comes to legends is to arrange them per order of appearance. 
    • Tooltip: A tooltip is a visualization technique that allows you to add extra information to your graphs to make them more clear. Now, adding them under each data point would totally overcrowed them. Instead, you should rely on interactive tooltips that show the extra text once the user hovers over the data point. 

    By following these best practices you will make sure your text brings an added value to your visuals instead of making them crowded and harder to read. 

    9. Include Comparisons

    This may be the briefest of our data visualization methods, but it’s important nonetheless: when you’re presenting your information and insights, you should include as many tangible comparisons as possible. By presenting two graphs, charts, and diagrams together, each showing contrasting versions of the same information over a particular timeframe, such as monthly sales records for 2016 and 2017 presented next to one another, you will provide a clear-cut guide on the impact of your data, highlighting strengths, weaknesses, trends, peaks, and troughs that everyone can ponder and act upon.

    10. Tell Your Tale

    Similar to content marketing, when you're presenting your data in a visual format with the aim of communicating an important message or goal, telling your story will engage your audience and make it easy for people to understand with minimal effort.

    Scientific studiesconfirm that humans, in large, respond better to a well-told story, and by taking this approach to your visualization pursuits, you will not only dazzle your colleagues, partners, and clients with your reports and presentations, but you will increase your chances of conveying your most critical messages, getting the buy-in and response you need to make the kind of changes that will result in long-term growth, evolution and success.

    To do so, you should collate your information, thinking in terms of a writer, establishing a clear-cut beginning, middle, and end, as well as a conflict and resolution, building tension during your narrative to add maximum impact to your various visualizations.

    11. Merge It All Together

    Expanding on the point above, in order to achieve an efficient data storytelling process with the help of visuals, it is also necessary to merge it all together into one single location. In the past, this was done with the help of endless PowerPoint presentations or Excel sheets. However, this is no longer the case thanks to modern dashboard technology. 

    Dashboards are analytical tools that allow users to visualize their most important performance indicators all on one screen. This way, you avoid losing time by looking at static graphs that make the process tedious. Instead, you get the possibility to interact and navigate them to extract relevant conclusions in real-time. Now, dashboard design has its own set of best practices that you can explore, however, they are still similar to the ones mentioned throughout this post.

    12. Consider The End Device

    As we almost reach the end of our list of insightful data visualization methods, we couldn’t leave a fundamental point behind. We live in a fast-paced world where decisions need to be made on the go. In fact, according to Statista, 56,89% of the global online traffic corresponds to mobile internet traffic. With that in mind, it is fundamental to consider device versatility when it comes to building your visuals and ensuring an excellent user experience.   

    We already mentioned the importance of merging all your visuals together into one intuitive business dashboard to tell a complete story. When it comes to generating visuals for mobile, the same principles apply. Considering that these screens are smaller than desktops, you should make sure to only include the graphs and charts that will help you convey the message you want to portray. You should also consider the size of labels and buttons as they can be harder to see on a smaller device. Once you have managed all these points, you need to test on different devices to ensure that everything runs smoothly.  

    13. Apply Visualization Tools For The Digital Age

    We live in a fast-paced, hyper-connected digital age that is far removed from the pen and paper or even copy and paste mentality of the yesteryears - and as such, to make a roaring visualization success, you should use the digital tools that will help you make the best possible decisions while gathering your data in the most efficient, effective way.

    A task-specific, interactive online dashboard or tool offers a digestible, intuitive, comprehensive, and interactive means of collecting, collating, arranging, and presenting data with ease - ensuring that your techniques have the most possible impact while taking up a minimal amount of your time.

    Summary

    As seen throughout this guide, data visualizations allow users and businesses to make large volumes of relevant data more accessible and understandable. With markets becoming more competitive by the day, the need to leverage the power of data analytics becomes an obligation instead of a choice, and companies that understand that will have a huge competitive advantage. 

    Author: Bernardita Calzon

    Source: Datapine

  • Dashboard storytelling: The perfect presentation (part 1)

    Dashboard storytelling: The perfect presentation (part 1)

    Plato famously said that “those who tell stories rule society.” This statement is as true today as it was in ancient Greece, perhaps even more so in modern times.

    In the contemporary world of business, the age-old art of storytelling is far from forgotten: rather than speeches on the Senate floor, businesses rely on striking data visualizations to convey information, drive engagement, and persuade audiences.

    By combining the art of storytelling with the technological capabilities of dashboard software, it’s possible to develop powerful, meaningful, data-backed presentations that not only move people but also inspire them to take action or make informed, data-driven decisions that will benefit your business.

    As far back as anyone can remember, narratives have helped us make sense of the sometimes complicated world around us. Rather than just listing facts, figures, and statistics, people used gripping, imaginative timelines, bestowing raw data with real context and interpretation. In turn, this got the attention of listeners, immersing them in the narrative, thereby offering a platform to absorb a series of events in their mind’s eye precisely the way they unfolded.

    Here we explore data-driven, live dashboard storytelling in depth, looking at storytelling with KPIs and the dynamics of a data storytelling presentation while offering real-world storytelling presentation examples.

    First, we’ll delve into the power of data storytelling as well as the general dynamics of a storytelling dashboard and what you can do with your data to deliver a great story to your audience. Moreover, we will offer dashboard storytelling tips and tricks that will help you make your data-driven narrative-building efforts as potent as possible, driving your business into exciting new dimensions. But let’s start with a simple definition.

    “You’re never going to kill storytelling, because it’s built in the human plan. We come with it.” – Margaret Atwood

    What is dashboard storytelling?

    Dashboard storytelling is the process of presenting data in effective visualizations that depict the whole narrative of key performance indicators, business strategies and processes in the form of an interactive dashboard on a single screen, and in real-time. Storytelling is indeed a powerful force, and in the age of information, it’s possible to use the wealth of insights available at your fingertips to communicate your message in a way that is more powerful than you could ever have imagined. So, let's take a look at the top tips and tricks to be able to successfully create your own story with a few clicks.

    4 Tricks to get started with dashboard storytelling

    Big data commands big stories.

    Forward-thinking business people turn to online data analysis and data visualizations to display colossal volumes of content in a few well-designed charts. But these condensed business insights may remain hidden if they aren’t communicated with words in a way that is effective and rewarding to follow. Without language, business people often fail to push their message through to their audience, and as such, fail to make any real impact.

    Marketers, salespeople, and entrepreneurs are today’s storytellers. They are wholly responsible for their data story. People in these roles are often the bridge between their data and the forum of decision-makers they’re looking to encourage to take the desired action.

    Effective dashboard storytelling with data in a business context must be focused on tailoring the timeline to the audience and choosing one of the right data visualization types to complement or even enhance the narrative.

    To demonstrate this notion, let’s look at some practical tips on how to prepare the best story to accompany your data.

    1. Start with data visualization

    This may sound repetitive, but when it comes to a dashboard presentation, or dashboard storytelling presentation, it will form the foundation of your success: you must choose your visualization carefully.

    Different views answer different questions, so it’s vital to take care when choosing how to visualize your story. To help you in this regard, you will need a robust data visualization tool. These intuitive aids in dashboard storytelling are now ubiquitous and provide a wide array of options to choose from, including line charts, bar charts, maps, scatter plots, spider webs, and many more. Such interactive tools are rightly recognized as a more comprehensive option than PowerPoint presentations or endless Excel files.

    These tools help both in exploring the data and visualizing it, enabling you to communicate key insights in a persuasive fashion that results in buy-in from your audience.

    But for optimum effectiveness, we still need more than a computer algorithm.. Here we need a human to present the data in a way that will make it meaningful and valuable. Moreover, this person doesn’t need to be a common presenter or a teacher-like figure. According to research carried out by Stanford University, there are two types of storytelling: author- and reader-driven storytelling.

    An author-driven narrative is static and authoritative because it dictates the analysis process to the reader or listener. It’s like analyzing a chart printed in a newspaper. On the other hand, reader-driven storytelling allows the audience to structure the analysis on their own. Here, the audience can choose the data visualizations that they deem meaningful and interact with them on their own by drilling down to more details or choosing from various KPI examples they want to see visualized. They can reach out for insights that are crucial to them and make sense out of data independently. A different story may need a different type of stoeytelling.

    2. Put your audience first

    Storytelling for a dashboard presentation should always begin with stating your purpose. What is the main takeaway from your data story? It should be clear that your purpose is to motivate the audience to take a certain action.

    Instead of thinking about your business goals, try to envision what your listeners are seeking. Each member of your audience, be that a potential customer, future business partner, or stakeholder, has come to listen to your data storytelling presentation to gain a profit for him or herself. To better meet your audience’s expectations and gain their trust (and money), put their goals first in the determination of the line of your story.

    Needless to say, before your dashboard presentation, try to learn as much as you can about your listeners. Put yourself in their shoes: Who are they? What do they do on a daily basis? What are their needs? What value can they draw from your data for themselves?

    The better you understand your audience, the more they will trust you and follow your idea.

    3. Don’t fill up your data storytelling with empty words

    Storytelling with data, rather than just presenting data visualizations, brings the best results. That said, there are certain enemies of your story that make it more complicated than enlightening and turn your efforts into a waste of time.

    The first things that could cause some trouble are the various technology buzzwords that are devoid of any defined meaning. These words don’t create a clear picture in your listeners’ heads and are useless as a storytelling aid. In addition, to under-informing your audience, buzzwords are a sign of your lazy thinking and a herald that you don’t have anything unique or meaningful to say. Try to add clarity to your story by using more precise and descriptive narratives that truly communicate your purpose.

    Another trap can be the use of your industry jargon to sound more professional. The problem here is that it may not be the jargon of your listeners’ industry, they may not comprehend your narrative. Moreover, some jargon phrases have different meanings depending on the context they are used in. They mean one thing in the business field and something else in everyday life. Generally they reduce clarity and can also convey the opposite meaning of what you intend to communicate in your data storytelling.

    Don’t make your story too long, focus on explaining the meaning of data rather than the ornateness of your language, and humor of your anecdotes. Avoid overusing buzzwords or industry jargon and try to figure out what insights your listeners want to draw from the data you show them.

    4. Utilize the power of storytelling

    Before we continue our journey into data-powered storytelling, we’d like to further illustrate the unrivaled the power of offering your audience, staff, or partners inspiring narratives by sharing these must-know insights:

    • Recent studies suggest that 80% of today’s consumers want brands to tell stories about their business or products.
    • The average person processes 100 to 500 digital words every day. By taking your data and transforming it into a focused, value-driven narrative, you stand a far better chance of your message resonating with your audience and yielding the results you desire.
    • Human beings absorb information 60 times faster with visuals than with linear text-based content alone. By harnessing the power of data visualization to form a narrative, you’re likely to earn an exponentially greater level of success from your internal or external presentations.

    Please also take a look at part 2 of this interesting read, including presentation tips and examples of dashboard storytelling.

    Author: Sandra Durcevic

    Source: Datapine

  • Dashboard storytelling: The perfect presentation (part 2)

    Dashboard storytelling: The perfect presentation (part 2)

    In the first part of this article, we have introduced the phenomenon of dashboard storytelling and some tips and tricks to get started with it. If you haven´t read part 1 of this article, make sure you do that! You can find part 1 here.

    How to present a dashboard – 6 Tips for the perfect dashboard storytelling presentation

    Now that we’ve covered the data-driven storytelling essentials, it’s time to dig deeper into ways that you can make maximum impact with your storytelling dashboard presentations.

    Business dashboards are now driving forces for visualization in the field of business intelligence. Unlike their predecessors, a state-of-the-art dashboard builder gives presenters the ability to engage audiences with real-time data and offer a more dynamic approach to presenting data compared to the rigid, linear nature of, say, Powerpoint for example.

    With the extra creative freedom data dashboards offer, the art of storytelling is making a reemergence in the boardroom. The question now is: What determines great dashboarding?

    Without further ado, here are six tips that will help you to transform your presentation into a story and rule your own company through dashboard storytelling.

    1. Set up your plan

    Start at square one on how to present a dashboard: outline your presentation. Like all good stories, the plot should be clear, problems should be presented, and an outcome foreshadowed. You have to ask yourself the right data analysis questions when it comes to exploring the data to get insights, but you also need to ask yourself the right questions when it comes to presenting such data to a certain audience. Which information do they need to know or want to see? Make sure you have a concise storyboard when you present so you can take the audience along with you as you show off your data. Try to be purpose-driven to get the best dashboarding outcomes, but don’t entangle yourself in a rigid format that is unchangeable.

    2. Don’t be afraid to show some emotion

    Stephen Few, a leading design consultant, explains on his blog that “when we appeal to people’s emotions strictly to help them personally connect with information and care about it, and do so in a way that draws them into reasoned consideration of the information, not just feeling, we create a path to a brighter, saner future”. Emotions stick around much longer in a person’s psyche than facts and charts. Even the most analytical thinkers out there will be more likely to remember your presentation if you can weave elements of human life and emotion. How to present a dashboard with emotion? By adding some anecdotes, personal life experiences that everyone can relate to, or culturally shared moments and jokes.

    However, do not rely just on emotions to make your point. Your conclusions and ideas need to be backed by data, science, and facts. Otherwise, and especially in business contexts, you might not be taken seriously. You’d also miss an opportunity to help people learn to make better decisions by using reason and would only tap into a “lesser-evolved” part of humanity. Instead, emotionally appeal to your audience to drive home your point.

    3. Make your story accessible to people outside your sector

    Combining complicated jargon, millions of data points, advanced math concepts, and making a story that people can understand is not an easy task. Opt for simplicity and clear visualizations to increase the level of audience engagement.

    Your entire audience should be able to understand the points that you are driving home. Jeff Bladt, the director of Data Products Analytics at DoSomething.org, offered a pioneering case study on accessibility through data. When commenting on how he goes from 350 million data points to organizational change, he shared: “By presenting the data visually, the entire staff was able to quickly grasp and contribute to the conversation. Everyone was able to see areas of high and low engagement. That led to a big insight: Someon outside the analytics team noticed that members in Texas border towns were much more engaged than members in Northwest coastal cities.”

    Making your presentation accessible to laypeople opens up more opportunities for your findings to be put to good use.

    4. Create an interactive dialogue

    No one likes being told what to do. Instead of preaching to your audience, enable them to be a part of the presentation througinteractive dashboard features. By using real-time data, manipulating data points in front of the audience, and encouraging questions during the presentation, you will ensure your audiences are more engaged as you empower them to explore the data on their own. At the same time, you will also provide a deeper context. The interactivity is especially interesting in dashboarding when you have a broad target audience: it onboards newcomers easily while letting the ‘experts’ dig deeper into the data for more insights.

    5. Experiment

    Don’t be afraid to experiment with different approaches to storytelling with data. Create a dashboard storytelling plan that allows you to experiment, test different options, and learn what will build the engagement among your listeners and make sure you fortify your data storytelling with KPIs (Key Performance Indicators). As you try and fail by making them fall asleep or check their email, you will only learn from it and get the information on how to improve your dashboarding and storytelling with data techniques, presentation after presentation.

    6. Balance your words and visuals wisely

    Last but certainly not least is a tip that encompasses all of the above advice but also offers a means of keeping it consistent, accessible, and impactful from start to finish balance your words and visuals wisely.

    What we mean here is that in data-driven storytelling, consistency is key if you want to grip your audience and drive your message home. Our eyes and brains focus on what stands out. The best data storytellers leverage this principle by building charts and graphs with a single message that can be effortlessly understood, highlighting both visually and with words the strings of information that they want their audience to remember the most.

    With this in mind, you should keep your language clear, concise, and simple from start to finish. While doing this, use the best possible visualizations to enhance each segment of your story, placing a real emphasis on any graph, chart, or sentence that you want your audience to take away with them.

    Every single element of your dashboard design is essential, but by emphasizing the areas that really count, you’ll make your narrative all the more memorable, giving yourself the best possible chance of enjoying the results you deserve.

    The best dashboard storytelling examples

    Now that we’ve explored the ways in which you can improve your data-centric storytelling and make the most of your presentations, it’s time for some inspiring storytelling presentation examples. Let’s start with a storytelling dashboard that relates to the retail sector.

    1. A retailer’s store dashboard with KPIs

    The retail industry is an interesting one as it has particularly been disrupted with the advent of online retailing. Collecting data analytics is extremely important for this sector as it can take an excellent advantage out of analytics because of its data-driven nature. And as such, data storytelling with KPIs is a particularly effective method to communicate trends, discoveries and results.

    The first of our storytelling presentation examples serves up the information related to customers’ behavior and helps in identifying patterns in the data collected. The specific retail KPIs tracked here are focused on the sales: by division, by items, by city, and the out-of-stock items. It lets us know what the current trends in customers’ purchasing habits are and allow us to break down this data according to a city or a gender/age for enhanced analysis. We can also anticipate any stock-out to avoid losing money and visualize the stock-out tendencies over time to spot any problems in the supply chain.

    2. A hospital’s management dashboard with KPIs

    This second of our data storytelling examples delivers the tale of a busy working hospital. That might sound a little fancier than it is, but it’s of paramount importance. All the more when it comes to public healthcare, a sector very new to data collection and analytics that has a lot to win from it in many ways.

    For a hospital, a centralized dashboard is a great ally in the everyday management of the facility. The one we have here gives us the big picture of a complex establishment, tracking several healthcare KPIs.

    From the total admissions to the total patients treated, the average waiting time in the ER, or broken down per division, the story told by the healthcare dashboard is essential. The top management of this facility have a holistic view to run the operations more easily and efficiently and can try to implement diverse measures if they see abnormal figures. For instance, an average waiting time for a certain division that is way higher than the others can shed light on some problems this division might be facing: lack of staff training, lack of equipment, understaffed unit, etc.

    All this is vital for the patient’s satisfaction as well as the safety and wellness of the hospital staff that deals with life and death every day.

    3. A human resources (HR) recruitment dashboard with KPIs

    The third of our data storytelling examples relates to human resources. This particular storytelling dashboard focuses on one of the most essential responsibilities of any modern HR department: the recruitment of new talent.

    In today’s world, digital natives are looking to work with a company that not only shares their beliefs and values but offers opportunities to learn, progress, and grow as an individual. Finding the right fit for your organization is essential if you want to improve internal engagement and reduce employee turnover.

    The HR KPIs related to this storytelling dashboard are designed to enhance every aspect of the recruitment journey, helping to drive down economical efficiencies and improving the quality of hires significantly.

    Here, the art of storytelling with KPIs is made easy. This HR dashboard offers a clear snapshot into important aspects of HR recruitment, including the cost per hire, recruiting conversion or success rates, and the time to fill a vacancy from initial contact to official offer.

    With this most intuitive of data storytelling examples, building a valuable narrative that resonates with your audience is made easy, and as such, it’s possible to share your recruitment insights in a way that fosters real change and business growth.

    Final words of advice

    One of the major advantages of working with dashboards is the improvement they have made to data visualization. Don’t let this feature go to waste with your own presentations. Place emphasis on making visuals clear and appealing to get the most from your dashboarding efforts.

    Transform your presentations from static, lifeless work products into compelling stories by weaving an interesting and interactive plot line into them.

    If you haven't read part 1 of this article yet, you can find it here.

    Author: Sandra Durcevic

    Source: Datapine

  • Data visualization is key: a prime example from the entertainment industry

    Data visualization is key: a prime example from the entertainment industry

    As we all know, Marvel is one of the most influential comic books in the world created by Stan Lee. Only a mind like his could create an out-of-this-world creation that would last forever. What’s amazing is that Marvel characters are developed through the influence of other Marvel heroes through data visualization.

    The dataset of Marvel is packed with a list of manifestations of their co-superheroes. For instance, when Spider-Man appears in a comic book with Captain America, these are all visualized through data graphics.

    This is essential since the Marvel Universe consists of thousands of unique universes and all the multiverse stories happened on earth. Through data visualization, they will know the heroes who are much more important than those with fewer priorities.

    Better Understanding of Marvel and Its Evolution with Big Data

    Marvel was first released as a comic book in October 1939 that featured a few superheroes, known as Human Torch and Sub-Mariner. In 1941, the Marvel comic released Captain America. However, the publisher of Marvel Comics named Goldman closed its door from publishing this kind of book in the early 1950s.

    The reason behind this is that readers lose interest in reading this kind of comic genre. However, in 1953 they tried to bring back superhero comics to the public and continued releasing a series of books about Captain America.

    As of today, many Marvel superheroes have their movies that gather more people to take an interest in Marvel. So, to know more about them, it’s best to go through the complete list of Marvel movies in order to learn about the backstories of different Marvel superheroes.

    Big data has become more important than ever in Marvel’s business model. More Marvel movies and comics are being adapted based on demographic data and data visualization.

    First Graphic Presentation

    To visualize the network, we need to first build a small web application using Python. Then, together with sigma.js and using the networkx package, we came up with the first graphic visualization. The node’s size represents the degree and the colors used on the node to graph detected clusters.

    With the help of this first graphical presentation, we can come up with a few hypotheses. This might be less interesting to you, but this graph visualization is indeed essential. Here are some of the findings:

    • Marvel characters who got the highest score on the social graph are Captain America, Spider-Man, and Iron Man. It means these are the most relevant heroes in the Marvel Universe. It is not a surprise anymore since they have been around the Comic series since the beginning.
    • Some characters who also received a high score from the social graph are Thor’s universe, The Avengers, Fantastic Four, and X-Men. Some small clusters are detected in the graph, and most of these characters are less popular, and some don’t even have a page on Wikipedia.

    Thus, this graphical visualization is essential to know how they will visualize the next Marvel film that Marvel fans will be a big hit.

    Shaping the Graph

    Using edge weights, we can shape the internal structure of the graph. Edge weight is the number of co-occurrences between heroes. Let’s say, for example, the edge-weight connection between Spider-Man and Captain America is the same as the number of series in comics they have been together.

    Thus, the more we increase the focus on a specific hero like Captain America, the graph will be much more clearer. In that way, the graph will only present the heroes with related data and connection with Captain America; heroes with less connection will disappear.

    Identifying the Marvel Influencers

    Through these graphs, we will clearly know how Marvel groups its superheroes in certain movies. There is broad research and has considered many statistics through social networks such as Twitter and Facebook to come up with these visualizations.

    A few graph criteria were presented to explain them: Page Rank, closeness centrality, and degree centrality. It also showed that the value of closeness centrality represents the node’s importance in the graph on how close the characters are to each other and those that aren’t connected.

    The final graph presented showed that Marvel, like Spider-Man, Hulk, and Thor, will be the best partners for movies. And if Beast would be the star of the show, surprisingly, he is not a good fit for X-Men, but rather perfect to bridge the link between Avengers and X-Men.

    Data Visualization is Key to Success in Social Media

    Based on the information presented above, graphical analysis using raw data is important to create a good plot for any Marvel movie. This might be the reason behind the great success of Marvel throughout the years. Without this smart data visualization considering thousands of characters related to Marvels, they will have a hard time grouping the characters.

    There is so much more about graphic visualization, and we only have presented the most basic explanation about how this process works. To know more about this topic, make sure to join different Marvel forums.

    Author: Kayla Matthews

    Source: Smart Data Collective

  • From Visualization to Analytics: Generative AI's Data Mastery

    From Visualization to Analytics: Generative AI's Data Mastery

    Believe it or not, generative AI is more than just text in a box. The truth is that it transcends the boundaries of traditional creative applications. So what it does is it extends the capabilities of the user far beyond text generation. It’s an art. In addition to its prowess in crafting captivating narratives and artistic creations, generative AI demonstrates its versatility by helping users empower their own data analytics. 

    With its advanced algorithms and language comprehension, it can navigate complex datasets and distill valuable insights. This transformative shift underscores the convergence of creativity and analysis, as generative AI empowers users to harness its intelligence for data-driven decision-making. 

    From uncovering hidden patterns to providing actionable recommendations, generative AI’s proficiency in data analytics heralds a new era where innovation spans the spectrum from artistic expression to informed business strategies. 

    So let’s take a brief look at some examples of how generative AI can be used for data analytics. 

    Datasets for Analysis

    Our first example is its capacity to perform data analysis when provided with a dataset. Imagine equipping generative AI with a dataset rich in information from various sources. Through its proficient understanding of language and patterns, it can swiftly navigate and comprehend the data, extracting meaningful insights that might have remained hidden by the casual viewer. Even experts can miss patterns after a while, but for AI, it’s made to detect them.

    All of this goes beyond mere computation. By crafting human-readable summaries and explanations, AI is able to make the findings accessible to a wider audience, especially to non-expert stakeholders who may not have a deep-level understanding of what they’re being shown. 

    This symbiotic fusion of data analysis and natural language generation underscores AI’s role as a versatile partner in unraveling the layers of information that drive informed decisions.

    Data Visualization Through Charts

    The second example of how generative AI is multifaceted is its ability to create user-friendly charts that seamlessly integrate with other data visualization tools. Suppose you have a dataset and require a visual representation that’s both insightful and easily transferable to other programs. Generative AI can step up to the plate by creating charts that are not only visually appealing but also tailored to your data’s characteristics. 

    Whether it’s a bar graph, scatter plot, or line chart, generative AI can provide charts ready for your preferred mode of visualization. This streamlined process bridges the gap between data analysis and visualization, empowering users to effortlessly harness their data’s potential for impactful presentations and strategic insights.

    Idea Generation

    This isn’t isolated to just data analytics. Most marketers have found that generative AI tools are great at this. That’s because the technology is great at helping its human users with idea generation and refining concepts by acting as a collaborative brainstorming partner. Consider a scenario where you’re exploring a new project or problem-solving endeavor. Engaging generative AI allows you to bounce ideas off of it, unveiling a host of potential questions and perspectives that might not have otherwise occurred to you. 

    Through its adept analysis of the input and context, generative AI not only generates thought-provoking questions but also offers insights that help you delve deeper into your topic. This relationship between the human user and the AI transforms generative AI into an invaluable ally, driving the exploration of ideas, prompting critical thinking, and guiding the conversation toward uncharted territories of creativity and innovation.

    Cleaning Up Data and Finding Anomalies

    As mentioned above, generative AI has a knack for finding patterns, and these patterns aren’t just isolated to being positive. With a good generative AI program, a data team can take on even the meticulous task of data cleaning and anomaly detection. Picture a dataset laden with imperfections and anomalies that could skew analysis results. The AI can be harnessed to comb through the data, identifying inconsistencies, outliers, and irregularities that might otherwise go unnoticed. 

    Again, AI has a keen eye for patterns and deviations to aid in ensuring the integrity of the dataset. Human error is human error, but with AI, that error can be reduced significantly. Furthermore, generative AI doesn’t just flag anomalies—it provides insights into potential causes and implications. This fusion of data cleaning and analysis empowers users to navigate the complexities of their data landscape with confidence, making informed decisions based on reliable, refined datasets.

    Creating Synthetic Data

    Synthetic data generation is yet another facet where generative AI’s adaptability shines. When faced with limited or sensitive datasets, the AI can step in to generate synthetic data that mimics the characteristics of the original information. This synthetic data serves as a viable alternative for training models, testing algorithms, and ensuring privacy compliance. By leveraging its understanding of data patterns and structures, 

    Generative AI crafts synthetic datasets that maintain statistical fidelity while safeguarding sensitive information. This innovative application showcases generative AI’s role in bridging data gaps and enhancing the robustness of data-driven endeavors, providing a solution that balances the need for accurate analysis with the imperative of data security.

    Conclusion

    Some great stuff huh? As you have just read, generative AI isn’t only for creating amazing images, or a chatbot that can help office workers with their tasks. It’s a technology that if utilized correctly can help any data professionals supercharge their data analytics. Now, are you ready to learn more?

    Date: September 22, 2023

    Author:

    Source: ODSC

  • How BI helps shaping the future of retail

    How BI helps shaping the future of retail

    The author of this article, Microstrategy's Nick Barth, joined DynamicAction and LEGO Group onstage at FT Future of Retail 2019 to discuss how to maximize the power of data-driven customer insights.

    The event discussion offered three main takeaways for retail enterprises looking to expand and optimize their data.

    Be smarter about how we look at data

    It's time to wean ourselves off of Excel. When all your data is in a spreadsheet, it's hard to find value within the rows and columns. There are much better ways of visualizing data today, and modern visualization tools benefit everyone in the enterprise with intelligence, not just the data-adept.

    Data lakes aren't the answer

    While a unified warehouse is challenging to achieve, data lakes haven't proven themselves to be better. Business users and analysts alike are referring to them as 'data swamps'. So how can enterprises turn disparate data from multiple sources, and at different levels of usability, into something that elevates the enterprise?

    The answer is an enterprise semantic layer: software that filters data from different sources and provides the governance necessary for a single version of the truth across the organization. When all users, from store managers to executives, are looking at the same numbers, you’re on your way to success as a retailer of the future.

    Keep a pulse on your business

    Retail business leaders need to be in the know about vital KPIs such as store performance and customer experience, and they need this data to be in real time, accurate, and easily accessible. Self-service BI makes this possible, but those looking to the future should take advantage of new technologies to not only make data accessible, but to integrate it into the natural workflow of every employee.

    So what concrete benefits will these important tips deliver to your retail enterprise? Here are three of many:

    • Competitive pricing: Flag pricingdiscrepancies and deliver the best possible value to your customers.
    • Real-time store performance monitoring: Mobile dashboards can deliver important store and customer KPIs to every employee on the floor, helping them boost the customer experience and drive sales.
    • Inventory management: Never experience a stockout again by arming your store ops and supply chain managers with the accurate inventory data they need to take collective action.

    The discussion at FT Future of Retail made it clear that the retail industry needs to embrace data and analytics to keep up with both competitors and consumer demands.

    Author: Nick Barth

    Source: MicroStrategy

  • The Advantages of (interactive) Data Visualization

    The Advantages of (interactive) Data Visualization

    Humans are visual creatures. A visual is processed 60,000 times faster than any form of text, and studies show that 65% of the population is composed of visual learners. Moreover, 90% of the information transferred to the brain is visual.

    Marrying digestible text with striking visuals provides the greatest results regarding the effective presentation of data, which in turn makes it easy for audiences to understand and retain data. This very notion is the core of visualization.

    In recent times, data visualization specialists have married information to high aesthetics, taking advantage of humans’ natural affinity for beauty. When we are choosing the right data visualization type, the most important element to consider is if you’re offering people the opportunity to see insights they haven’t seen or experienced before and wouldn’t otherwise be able to decipher in written text alone.

    Creators of effective visuals understand our human predisposition for the visual, taking it a step further by adding interactive functionalities that capture the imagination while presenting critical insights in a way that is as inspiring as it is understandable. By scrolling, clicking, and moving the cursor over interesting data points, designers engage users on a deeper level and enable them to be a participant rather than a viewer alone, adding more meaning to the data discovery learning process as a result.

    Studies suggest that those who follow directions with illustrations perform 323% more efficiently than those who follow text-only directions. To demonstrate, here we place the spotlight on 24 of the best data visualization examples from around the globe. Whether static or interactive dashboards, these creative data visualization samples will serve as an inspiration for any data enthusiast. 

    The Benefits Of Data Visualization

    Before we delve any deeper, we’re going to look at the primary benefits of taking an active:

    • Quicker action: As mentioned, the human brain processes visual information faster than text-based one, which means that your stakeholders – internally – or your prospects – externally – will be able to digest fresh insights and take swift, positive action on them.
    • Finding connections: By displaying data in an inspiring visual format, it will be far easier to spot correlations and find connections between your operations and your overall commercial performance. As a result, you can develop a management report that will enable you to gain the insights you need to make changes that have a positive impact on the business.
    • Emerging trends: By curating your data dashboards and presenting them visually, you stand a greater chance of spotting the kind of market trends that you can use to evolve your efforts while boosting profitability and gaining an edge over your competitors.
    • Fresh discussions: One of the most beneficial elements of using visuals is the fact that it allows you to tell a story with your insights and, as a result, drill down deeper into specific segments of data. By utilizing your own dashboard storytelling efforts, you will be able to spot fresh insights and spark new discussions based on the growth, development, and direction of your business. Moreover, with the use of inspirational, informational graphics, you’ll engage your target audience on a deeper level, encouraging the kind of online discussions that will boost brand awareness, expand your reach, and help you position yourself as a thought leader in your field.

    Data Visualization Today: Why It Matters

    Good visualizations are particularly important in business, where large volumes of data must be analyzed swiftly or presented in a clear and actionable format. The rows of numbers alone won’t create a story compelling enough to catch the audience’s attention. The goal is always to make the data behind your arguments look attractive enough to persuade decision-makers or enlighten your team members. With easy-to-use interactive data visualization software more and more companies can create eye-catching visualizations on their own. Interactive interfaces make it possible even for non-technical users to create actionable charts.

    The type of visualization you select is guided by the kind of information you are seeking to convey. A fixed image is ideal when alternate views are neither needed nor desired, and when publishing to a static medium, such as print. Dynamic, interactive visualizations are better for empowering people to explore the data for themselves. Both have their advantages. When creating one, the purpose should always be to generate a certain level of excitement and engagement with the audience, for it to be the best visualization.

    Interactive Data Visualization: What’s In It For Me?

    Combine Time and Motion to Aid Audience Understanding

    A layer of interactivity enables your audience to connect directly with your data and offers a second axis to track information changing over time. Hans Rosling, a famous data scientist, and visualization Ted Talker is a huge proponent of showing the time as a graphic movement. Check out this video – The Joy of Stats – a perfect example of how combining time with your visualization enables the viewer to see trends.

    Drilling Down to Extract Meaning From Numbers

    A trend we are seeing in all content marketing, not just visualization, is personal attention. Content is no longer a one-size-fits-all solution from customized white papers to interactive ebooks. Interactive visualization enables you to reach your audience on different levels by offering an ability to drill down into the data. Newcomers to the topic can still spot trends and learn the basics, while experts in the field can drill down deeper into the data for more insight.

    Engage, Engage, Engage

    Content marketing is competitive. There is a lot of noise to push through before you can be heard. The best interactive data visualization is a ticket into the spotlight. Let’s take, for example, USA Today’s interactive story “Behind The Bloodshed.” Mass killings dominate the American media. How can you compete with major prime channels as a newspaper? The USA upped the ante with this piece, particularly the interactive data visualization that enables the viewer to drill down on the mass killing timeline for details. The piece is informative, powerful, and emotional.

    Our selection of the best visualization examples above demonstrates creative, innovative leaps that illustrate the changing way we see and interpret data.

    Everything is becoming personalized. People want to see how they fit into the big picture, and where they stand on the shifting terrain. A real-time visualization example or some of the best interactive visualizations answer that need in two ways: giving the viewers control over what they see, and letting them narrow the data down to their personal situation, whether it is age, location, income, or other factors.

    This is the beginning of a new phase of data personalization. In place of abstract headlines and generic pronouncements, readers will be able to project themselves into the dataset. With the right tools, you can prepare the best interactive data visualizations for your business on your own, within a few clicks, and with no advanced IT skills needed.

    Author: Bernardita Calzon

    Source: Datapine

  • Why BI reporting is superior to traditional reporting

    Why BI reporting is superior to traditional reporting

    The pandemic has caused a major change in the way we do business. Some organizations had already begun the digitization journey before the pandemic hit, providing them with a head start or those that have managed to rapidly digitize has helped their business survive and enabled people to work remotely. Some of the requirements included using cloud technology to store and analyze large volumes of data which can be accessed by employees, partners and other stakeholders. People cannot afford to wait for weekly or monthly reports to make critical company decisions or need to see this information at home.  The ability to generate accurate, relevant and timely reports is critical if a company is to remain agile. In this post, we will discuss a few ways BI reporting is superior to traditional reporting practices.  

    The ability to turn raw company data into actionable intelligence is at the core of today’s successful businesses.

    Data is increasingly more important to everyone’s role. Its value is in helping people do their jobs better and BI reporting provides a complete picture of how your business is performing.

    BI reporting offers one source of the truth

    Companies often have data stored in multiple sources such as ERP, CRM and third party. Traditionally, data must be combined manually into a single source, typically a spreadsheet.  While spreadsheets have their uses, they are notoriously error-prone and not a good option for reporting. A mistake in a single cell will invalidate the entire report. Additionally, multiple managers will often share a spreadsheet. However, when multiple versions of the same document are created, it’s nearly impossible to guarantee that everyone is using the most current version.

    On the other hand, BI reporting integrates company data from multiple sources, so users always have access to one source of the truth. By consolidating disparate data into one discrete repository, data cannot be accidentally deleted or altered. Also, data is displayed on a BI dashboard in real-time so everyone works from the most current information.  

    BI reporting is on demand 

    As many executives know, traditional reporting is slow, rigid, and becomes outdated quickly.  Long, and often frustrating, wait times for IT generated reports are all too familiar experiences. Yet, executives and managers must rely on weekly, monthly, and annual reports to make critical business decisions. This can lead to missed opportunities.

    In contrast, BI reporting enables everyone to access data, conduct analysis, and create personalized reports without IT involvement. Self-service eliminates the wait time for IT reports. Instead, users can slice and dice the most current data whenever they need real-time, actionable insights. Also, standard reports can be generated on a designated schedule. For instance, reports can be set to generate on Monday mornings in anticipation of weekly staff meetings. If more information is needed during the meeting, a customized report can be created on the spot with just a few clicks.  

    Finally, free of the continuous demand for reports, the IT department has more time to focus their attention on other important tasks such as maintaining security or managing data resources. And, the IT department can apply BI reporting to develop strategies to grow the business and increase profitability. 

    BI reporting gives granular insight

    Traditional reports are static, only providing a summary of information without much detail. This means you cannot investigate which underlying factors are driving what you are observing.  Furthermore, static reports only provide the information you request. Since you can’t probe information you don't know is there, you are only getting half the story. A partial picture can lead to a wealth of missed opportunities.

    Conversely, BI reporting is dynamic allowing users to select a metric and drill down into the underlying data. In this way, users are empowered to ask questions of the data and follow their train of thought to discover the answers. For instance, overall sales figures may be on target. However, drilling down will display sales figures by region, product line, and type. This detailed analysis might reveal the one product is over-performing, and that this is masking the declining sales of another product. With this level of granular insight, the sales team can work to boost the sales of the underperforming product to increase sales revenue overall.

    BI reporting offers data visualizations

    BI reporting presents data in the form of visualizations to help clarity complex information. A graphical depiction of numbers makes the information easier to digest, retain, and recall. Visualizations might be simple bar charts, pie charts, and maps. Or they might be more complex models such as waterfalls, funnels, gauges, depending on your needs. In either case, your team will be able to see all factors that are affecting performance.  Visualization makes it easier to identify patterns, trends, and new opportunities. They offer the ability to see changes in customer behavior so your team can respond in ways that drive sales and enable you to stay ahead of the competition.

    BI reporting for month-end statements

    Finance team using a BI tool to report on month's close can review and analyze financial statements directly. A BI tool with financial statement capability makes month-end financial statements more accessible and allows more people to understand the impact of operational decisions on financial performance faster.

    By adding financial statements to business intelligence software brings active analysis, data drill down and dashboarding to the finance and management team with fully controlled user-permission.

    Financial statements are created in the same tradition as the accounting team recognizes, but the process is automated for each statement. The finance team can quickly build financial statements customized to users’ access, so branch managers can see information relevant to their branch, and management can see information across the whole business. The statements can also sit across one or many ERPs so leaders can view the individual company, branch, regional performance and even the consolidated performance when required.

    Now that preparing the financial statements is faster and simpler, the finance team has time to carry out in-depth analysis of the numbers. By preparing financial statements within a data analytics environment, you can quickly compare statements from one traditional period or outside of these timeframes - say one week to the next.

    Transitioning from traditional reporting to BI reporting will provide the ability to see the whole truth, make better decisions faster and uncover new business opportunities.

    Source: Phocas Software

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