With Big Data analytics solutions increasingly being made available to enterprises in the cloud, more and more companies will be able to afford and use them for agility, efficiency and competitiveness

On 27 September, enterprise software company SAP SE completed the acquisition of Altiscale Inc.—a provider of Big Data as-a-Service (BDaaS). The news came close on the heels of data management and analytics company Cloudera Inc. and data and communication services provider CenturyLink Inc. jointly announcing BDaaS services. Another BDaaS vendor, Qubole Inc., said it would offer a big data service solution for the Oracle Cloud Platform.

These are cases in point of the growing trend to offer big data analytics using a cloud model. Cloud computing allows enterprises to pay for software modules or services used over a network, typically the Internet, on a monthly or periodical basis. It helps firms save relatively larger upfront costs for licences and infrastructure. Big Data analytics solutions enable companies to analyse multiple data sources, especially large data sets, to take more informed decisions.

According to research firm International Data Corporation (IDC), the global big data technology and services market is expected to grow at a compound annual growth rate (CAGR) of 23.1% over 2014-2019, and annual spending is estimated to reach $48.6 billion in 2019.

With Big Data analytics solutions increasingly being made available to enterprises in the cloud, more and more companies will be able to afford and use them for agility, efficiency and competitiveness.

MarketsandMarkets, a research firm, estimates the BDaaS segment will grow from $1.8 billion in 2015 to $7 billion in 2020. There are other, even more optimistic estimates: research firm Technavio, for instance, forecasts this segment to grow at a CAGR of 60% from 2016 to 2020.

Where does this optimism stem from?

For almost 10 years, it was only the biggest of technology firms such as Alphabet Inc.’s Google and Amazon.com Inc., that used data analytics on a scale that justified the idea of ‘big’ in Big Data. In industry parlance, three key attributes are often used to understand the concept of Big Data. These are volume, velocity and variety of data—collectively called the 3Vs.

Increasingly, not just Google and its rivals, but a much wider swathe of enterprises are storing, accessing and analysing a mountain of structured and unstructured data. The trend is necessitated by growing connectivity, falling cost of storage, proliferation of smartphones and huge popularity of social media platforms—enabling data-intensive interactions not only among ‘social friends’ but also among employers and employees, manufacturers and suppliers, retailers and consumers—virtually all sorts of connected communities of people.

 

A November 2015 IDC report predicts that by 2020, organisations that are able to analyse all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their less analytically oriented peers.

The nascent nature of BDaaS, however, is causing some confusion in the market. In a 6 September article onNextplatform.com, Prat Moghe, founder and chief executive of Cazena—a services vendor—wrote that there is confusion regarding the availability of “canned analytics or reports”. According to him, vendors (solutions providers) should be carefully evaluated and aspects such as moving data sets between different cloud and on-premises systems, ease of configuration of the platform, etc., need to be kept in mind before making a purchase decision.

“Some BDaaS providers make it easy to move datasets between different engines; others require building your own integrations. Some BDaaS vendors have their own analytics interfaces; others support industry-standard visualization tools (Tableau, Spotfire, etc.) or programming languages like R and Python. BDaaS vendors have different approaches, which should be carefully evaluated,” he wrote.

Nevertheless, the teething troubles are likely to be far outweighed by the benefits that BDaaS brings to the table. The key drivers, according to the IDC report cited above, include digital transformation initiatives being undertaken by a lot of enterprises; the merging of real life with digital identity as all forms of personal data becomes available in the cloud; availability of multiple payment and usage options for BDaaS; and the ability of BDaaS to put more analytics power in the hands of business users.

Another factor that will ensure growth of BDaaS is the scarcity of skills in cloud as well as analytics technologies. Compared to individual enterprises, cloud service providers such as Google, Microsoft Corp., Amazon Web Services and International Businsess Machines Corp. (IBM) can attract and retain talent more easily and for longer durations.

Manish Mittal, managing principal and head of global delivery at Axtria, a medium-sized Big Data analytics solutions provider, says the adoption of BDaaS in India is often driven by business users. While the need is felt by both chief information officers and business leaders, he believes that the latter often drive adoption as they feel more empowered in the organisation.

The potential for BDaaS in India can be gauged from Axtria’s year-on-year business growth of 60% for the past few years—and there are several niche big data analytics vendors currently operating in the country (besides large software companies).

Mittal says that the growth of BDaaS adoption will depend on how quickly companies tackle the issue of improving data quality.

Source: livemint.com, October 10, 2016

 

To really make the most of big data, most businesses need to invest in some tools or services - software, hardware, maybe even new staff - and there's no doubt that the costs can add up. The good news is that big data doesn't have to cost the Earth and a small budget needn't prevent companies from stepping into the world of big data. Here are some tips and ideas to help keep costs down:

Think about your business objectives
Too many businesses focus on collecting as much data as possible which, in my view, misses the whole point of big data. The objective should be to focus on the data that helps you achieve your strategic objectives. The whole point of big data should be to learn something from your data, take action based on what you've learned and grow your business as a result. Limiting the scope of your data projects so they tightly match your business goals should help keep costs down, as you can focus only on the data you really need.

Make use of the resources you already have
Before you splash out on any new technology, it's worth looking at what you're already using in your business. Some of your existing infrastructure could have a role to play. Go through each of the four key infrastructure elements (data sources, data storage, data analysis and data output) and note what related technology or skills you already have in-house that could prove useful. For example, you may already be collecting useful customer data through your website or customer service department. Or you very likely have a wealth of financial and sales data that could provide insights. Just be aware that you may already have some very useful data that could help you achieve your business objectives, saving you time and money.

Look for savings on software
Open source (free) software, like Hadoop, exists for most of the essential big data tasks. And distributed storage systems are designed to run on cheap, off-the-shelf hardware. The popularity of Hadoop has really opened big data up to the masses - it allows anyone to use cheap off-the-shelf hardware and open source software to analyse data, providing they invest time in learning how. That's the trade-off: it will take some time and technical skill to get free software set up and working the way you want. So unless you have the expertise (or are willing to spend time developing it) it might be worth paying for professional technical help, or 'enterprise' versions of the software. These are generally customised versions of the free packages, designed to be easier to use, or specifically targeted at various industries.

Take advantage of big data as a service (BDaaS)
In the last few years many businesses have sprung up offering cloud-based big data services to help other companies and organisations solve their data dilemmas. This makes big data a possibility for even the smallest company, allowing them to harness external resources and skills very easily. At the moment, BDaaS is a somewhat vague term often used to describe a wide variety of outsourcing of various big data functions to the cloud. This can range from the supply of data, to the supply of analytical tools which interrogate the data (often through a web dashboard or control panel) to carrying out the actual analysis and providing reports. Some BDaaS providers also include consulting and advisory services within their BDaaS packages.

BDaaS removes many of the hurdles associated with implementing a big data strategy and vastly lowers the barrier of entry. When you use BDaaS, all of the techy 'nuts and bolts' are, in theory, out of sight and out of mind, leaving you free to concentrate on business issues. BDaaS providers generally take this on for the customer - they have everything set up and ready to go - and you simply rent the use of their cloud-based storage and analytics engines and pay either for the time you use them or the amount of data crunched. Another great advantage is that BDaaS providers often take on the cost of compliance and data protection - something which can be a real burden for small businesses. When the data is stored on the BDaaS provider's servers, they are (generally) responsible for it.

It's not just new BDaaS companies which are getting in on the act; some of the big corporations like IBM and HP are also offering their own versions of BDaaS. HP have made their big data analytics platform, Haven, available entirely through the cloud. This means that everything from storage to analytics and reporting is handled on HP systems which are leased to the customer via a monthly subscription - entirely eliminating infrastructure costs. And IBM's Analytics for Twitter service provides businesses with access to data and analytics on Twitter's 500 million tweets per day and 280 million monthly active users. The service provides analytical tools and applications for making sense of that messy, unstructured data and has trained 4,000 consultants to help businesses put plans into action to profit from them.

As more and more companies realise the value of big data, more services will emerge to support them. And competition between suppliers should help keep subscription prices low, which is another advantage for those on a tight budget. I've already seen that BDaaS is making big data projects viable for many businesses that previously would have considered them out of reach - and I think it's something we'll see and hear a lot more about in the near future.

Source: HuffPost