Making your Organization more intelligent with a Cloud Data Strategy
At a time when most major companies are showing a long-range commitment to “data-driven culture,” data is considered the most prized asset. An Enterprise Data Strategy, along with aligned technology and business goals, can significantly contribute to the core performance metrics of a business. The underlying principles of an Enterprise Data Strategy comprise a multi-step framework, a well-designed strategy process, and a definitive plan of action. However, in reality, very few businesses today have their Data Strategy aligned with overall business and technology goals.
Data Management Mistakes Are Costly
Unless the overall business and technology goals of a business are aligned with a Data Strategy, the business may suffer expensive Data Management failure incidents from time to time. If the Data Strategy is implemented in line with a well-laid out action plan that seeks to transform the current state of affairs into “strategic Data Management initiatives” leading to the fulfillment of desirable business needs and objectives in the long term, then there is a higher chance of that Data Strategy achieving the desired outcomes.
Data provides “insights” that businesses use for competitive advantage. When overall business goals and technology goals are left out of the loop of an Enterprise Data Strategy, the data activities are likely to deliver wrong results, and cause huge losses to the business.
What Can Businesses Do to Remain Data-Driven?
Businesses that have adopted a data-driven culture and those expecting to do so, can invest some initial time and effort to explore the underlying relationships between the overall business goals, technology goals, and Data Strategy goals. The best part is they can use their existing advanced analytics infrastructure to make this assessment before drafting a policy document for developing the Data Strategy.
This initial investment in time and effort will go a long way toward ensuring that the business’s core functions (technology, business, and Data Science) are aligned and have the same objectives. Without this effort, the Data Strategy can easily become fragmented and resource-heavy—and ineffective.
According to Anthony Algmin, Principal at Algmin Data Leadership, “Thinking of a Data Strategy as something independent of Business Strategy is a recipe for disaster.”
Data Governance has recently become a central concern for data-centric organizations, and all future Data Strategies will include Data Governance as a core component. The future Data Strategy initiatives will have to take regulatory compliances seriously to ensure long-term success of such strategies. The hope is that this year, businesses will employ advanced technologies like big data, graph, and machine learning (ML) to design and implement a strong Data Strategy.
In today’s digital ecosystem, the Data Strategy means the difference between survival and extinction of a business. Any business that is thinking of using data as a strategic asset for predetermined business outcomes must invest in planning and developing a Data Strategy. The Data Strategy will not only aid the business in achieving the desired objectives, but will also keep the overall Data Management activities on track.
A Parallel Trend: Rapid Cloud Adoption
As Data Strategy and Data Governance continue to gain momentum among global businesses, another parallel trend that has surfaced is the rapid shift to cloud infrastructures for business processing.
With on-premise Data Management practices, Cloud Data Management practices also revolve around MDM, Metadata Management, and Data Quality. As the organizations continue their journey to the cloud, they will need to ensure their Data Management practices conform to all Data Quality and Data Governance standards.
A nagging concern among business owners and operators who have either shifted to the cloud or are planning a shift is data security and privacy. In fact, many medium or smaller operations have resisted the cloud as they are unsure or uninformed about the data protection technologies available on the cloud. Current businesses owners expect cloud service providers to offer premium data protection services.
The issues around Cloud Data Management are many: the ability of cloud resources to handle high-volume data, the security leaks in data transmission pipelines, data storage and replication policies of individual service providers, and the possibilities of data loss from cloud hosts. Cloud customers want uninterrupted data availability, low latency, and instant recovery—all the privileges they have enjoyed so far in an on-premise data center.
One technology solution often discussed in the context of cloud data protection is JetStream. Through a live webinar, Arun Murthy, co-founder and Chief Product Officer of Horton Works, demonstrated how the cloud needs to be a part of the overall Data Strategy to fulfill business needs like data security, Data Governance, and holistic user experience. The webinar proceedings are discussed in Cloud Computing—an Extension of Your Data Strategy.
Cloud Now Viewed as Integral Part of Enterprise Data Strategy
One of the most talked about claims made by industry experts at the beginning of 2017 was that it “would be a tipping point for the cloud.” These experts and cloud researchers also suggested that the cloud would bring transformational value to business models through 2022, and would become an inevitable component of business models. According to market-watcher Forrester, “cloud is no longer about cheap servers or storage, (but), the best platform to turn innovative ideas into great software quickly.
As cloud enables big data analytics at scale, it is a popular computing platform for larger businesses who want the benefits without having to make huge in-house investments. Cloud holds promises for medium and small businesses, too, with tailor-made solutions for custom computing needs at affordable cost.
The following points should be kept in mind while developing a strategy plan for the cloud transformation:
- Consensus Building for Cloud Data Strategy: The core requirement behind building a successful Data Strategy for the cloud is consensus building between the central IT Team, the cloud architect, and the C-Suite executives. This problem is compounded in cases where businesses may be mix-matching their cloud implementations.
- Data Architectures on Native Cloud: The news feature titled Six Key Data Strategy Considerations for Your Cloud-Native Transformation throws light on cloud-native infrastructure, which is often ignored during a business transformation. According to this article, though enterprises are busy making investments in a cloud-native environment, they rarely take the time to plan the transformation, thus leaving Data Architecture issues like data access and data movement unattended.
- Creating Data Replicas: Data replication on the cloud must avoid legacy approaches, which typically enabled data updating after long durations.
- Data Stores across Multiple Clouds: HIT Think: How to Assess Weak Links in a Cloud Data Strategy specifically refers to storage of healthcare data, where data protection and quick data recovery are achieved through the provisioning of multiple cloud vendors. These solutions are not only cost-friendly, but also efficient and secure.
Author: Paramita (Guha) Ghosh