As we saw in 2017, enterprises are increasingly capitalizing on golden opportunities to tap big data for a growing array of business endeavors. Along the way, they’re strategically leveraging big data insights to make smarter business decisions. But what can enterprises expect next year? Here are three predictions about the future of big data in 2018.
Over the past 15 years, enterprises have continually invested in data warehouses, data lakes, data marts, and now the cloud—all with the hope of gaining integrated analytics and a strategic competitive advantage. During that time, however, entropy has set in. A business may now be contending with multiple sets of analytics, multiple data stores, and no real incentive to make their data organization methods more manageable.
This data sprawl becomes even more unwieldy as enterprises grapple with a tangled web of security governance requirements, such as tracking data to comply with GPDR. This dynamic can also create vendor lock-in: a business relying on cloud vendor–specific tools or software stacks. The cloud certainly offers powerful advantages, but it may tilt toward being too much of a good thing.
To get out in front of this, businesses should acknowledge that data sprawl is a natural force in their environment. From there, they need to figure out the best way to manage that force and even leverage it by considering what architectures and processes are most relevant in that space. This requires a new kind of thinking about data governance.
Data governance will profoundly affect the future of big data far beyond 2018. Data governance involves tagging and protecting enterprise data in order to understand where it came from, who had access to it, who modified it, and where it went. That creates traceability, provenance, even contextual data access, privacy, and security—all things that are going to be incredibly important for companies well into the future.
Until recently, data governance had a limited purview. It was a very clearly delineated and easy-to-implement process because the business created, owned, and defined the boundaries of all of its data. But thanks to the Internet of Things (IoT) and today’s social world, sensitive data can be created outside the firewall without any specific control. And with the rise in high-profile data breaches, businesses are realizing the acute need for better data governance.
Additionally, as businesses deal with the implementation of the GDPR, greater traceability will be important. All of these trends point to the increasing importance and changing nature of data governance within the enterprise.
When a business recognizes that data is a valuable and important asset, it treats data with the highest level of visibility and defines business and executive strategies around it. Businesses that adopt better data governance strategies will be well-positioned to smoothly navigate potential challenges while keeping a lid on costs
In today’s world, businesses must land the data first, then apply data science to it to define the necessary requirements. It’s a flipped way of thinking about the way enterprises need the process to behave: it’s really about letting the raw material lead to new use cases for the business.
Enterprises should prepare for the coming wave of big data generated by connected consumer devices, whether by proactively defining their data architecture or by identifying new lines of business to compete effectively in the market. According to ZDNet, IoT devices outnumbered the world’s population for the first time in 2017. When the data tipping point arrives, it will be orders of magnitude bigger than the industrial internet, which is already massive.
Businesses will have to re-evaluate how their infrastructure is designed in order to successfully navigate this change. Until now, the focus was always on converging and consolidating data—for example, through enterprise data warehousing and analytics. The new paradigm’s focus will be onboarding and connecting, whether it’s sensor data that’s captured and on-boarded in the cloud or traditionally housed inside a firewalled data center. Being able to capture data in its native form and then build out the tools and architectures to appropriately connect that data is a defining differentiation for modern-day architecture.
This challenge can be met with a dataplane approach, which transforms governance, security, and provisioning into a cloud service that can traverse multiple instances. It’s a key enabler for connecting data and analytics across multiple physical platforms on-premises or in the cloud. It also simplifies how enterprises deal with data sprawl by creating a single control point for managing those important processes. Finally, because the dataplane provides consistency of provisioning, it enables application portability. That way, you can move applications to data—not the other way around. In a connected world, that’s crucial.
The future of big data includes several important changes and trends that enterprises should begin preparing for now. How will your business maximize the opportunities that big data offers in 2018?
Read more about the best practices for becoming a data-driven organization in order to advance your enterprise in the new year.