Data Analytics Stack Goes Multicloud in 2022: Three Trends to Watch
The modern data analytics stack is undergoing shocks as the requirements imposed by a hybrid multicloud world upon data analytics become more apparent. What's ahead in 2022?
- By Kendall Clark
- December 9, 2021
Last year the entire world was struggling with the initial shocks of a global pandemic that everyone hoped would be well in hand in 2021. Although it's not clear where the pandemic is headed, supply chain shocks are still reverberating globally. As enterprises struggle to keep up, the modern data analytics stack is undergoing shocks of its own as the requirements imposed upon data analytics by a hybrid multicloud world become more apparent. In 2022, we expect to see an acceleration and intensification of the following three trends.
Trend #1: The rise of the just-in-time data analytics stack
There's a small but fast-growing segment of the data analytics space focused on new approaches to the enterprise stack. These new approaches include, of course, continuing to move all the things to the cloud. That's not new. What is new, however, is the awareness that there isn't just one cloud and that the hybrid multicloud imposes requirements of its own. Perhaps the primary requirement is the ability to manage and analyze data no matter where it lives in the hybrid multicloud environment. Everything is moving to the hybrid multicloud. That means a new approach to data analytics (including integration, search, query, AI/ML, and even reporting) is making where data lives less crucial -- and less impactful -- than what it means.
There are at least 10 new start-ups building platforms designed to query, search, connect, analyze, and integrate data where it lies without moving or copying it in a just-in-time fashion. These start-ups range from traditional OLAP data cube analytics in a data warehouse to search and NoSQL data storage, as well as data fabric and knowledge graph methods for integrating and connecting data. In a world where the number of places data may reside in storage is increasing rather than decreasing, we will see enterprises reach for data analytics solutions that are not coupled to where data lives.
The value of data-driven decision making and analytics is key to competitiveness in the knowledge economy, which means enterprise software vendors are racing to see who can drive down the time and cost of generating insight using enterprise data. This trend will accelerate in 2022 as data movement between storage systems occurs with diminished frequency, and is less central to the data stack, in order to accelerate time to insight.
Trend #2: The era of big data centralization and consolidation is over
Connected to the previous trend, and both accelerating it and being accelerated by it, is the decreased importance of centralized or consolidated data storage. To be clear, this trend isn't the end of storage. There will never be an end of storage. Rather this trend is the end of centrally consolidated approaches to data storage, particularly for analytics and application development.
In 2022, we will see the continuation of the big fight that's brewing in the data analytics space as old ways of managing enterprise data -- focusing on patterns of consolidation and centralization -- reach a peak and then start to trend downward. Part of what we're about to see unfold in the big fight between Snowflake and Databricks in 2022 and beyond is a function of their differing approaches to centralized consolidation. Snowflake is emblematic of the conventional approach using its powerful cloud-based data warehouse.
However, a data warehouse requires data consolidation. A cloud-based data warehouse requires data consolidation in a single cloud. Databricks, however, features a more decentralized, computationally intensive approach, owing to its heritage as the Apache Spark company. Other vendors are challenging even more thoroughly the requirement that data has be to centrally consolidated before it can be managed, as described in Trend #1.
It's not just technical pressures. The economics of unavoidable data movement in a hybrid multicloud world are not good and don't look to be improving. Customers and investors are pushing back against the kind of lock-in that accompanies centralization approaches. Something has to give in this battle and we anticipate the pendulum swinging in the direction of decentralization and disintermediation of the data analytics stack.
Trend #3: Data fabric goes mainstream
Data fabric is the future of data management according to analysts, but when will that future arrive and when will it be evenly distributed? The third trend we expect to see in 2022 is enterprise data fabric will arrive to more evident commercial maturity as the key to data integration in the hybrid multicloud world. Among the many signs, we will see increasing analyst attention on this growing part of the data analytics stack, including case studies of real-world adoption and total addressable market projections. Expect to see significant ROI studies from vendors in the space as well.
Next year will also bring high-profile enterprise adoption involving use cases such as analytics modernization, acceleration of insights from data lakes, digital twins in manufacturing and supply chain, as well as drug discovery and the supply chain control tower in pharma and life sciences.
It's perhaps ironic that all the innovation in data in the past 20 years has been focused -- some might say over-focused -- on the analytics components of the stack, and those are certainly crucial components.
However, just as race cars without high-octane fuel sources are no more than beautiful, static sculptures, analytics platforms such as AI/ML without total data mastery, accessibility, and innovative data integration solutions will fail to live up to their potential. Many market signals suggest that in 2022, the enterprise itself will get serious about finding new ways to integrate and connect data in the new hybrid multicloud world we live in.
These three trends are distinct but also interrelated. We've seen many exogenous shocks to the global enterprise "sense-making" machinery from the pandemic and associated challenges. This has rapidly accelerated awareness that the world has changed, and we're living in a new hybrid multicloud reality. This change, which has been focused on the lower levels of the IT stack -- that is to say, data centers, networks, raw storage, and computational resources -- is now making its way "up stack" and impacting both how we analyze and how we integrate data. All signs point toward an acceleration of this change in 2022.
Kendall Clark is founder and CEO of Stardog, a leading enterprise knowledge graph (EKG) platform provider. For more information visit www.stardog.com or follow them on Twitter.