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Data Analytics Trends to Watch in 2022

Last year the whole world grappled with the first shocks of a global pandemic that everyone hoped would be well under control in 2021. Although it is unclear where the pandemic is headed, supply chain shocks still resonate around the world. . , the modern data analytics stack is experiencing its own crashes, as the requirements for data analysis in a hybrid multicloud world are becoming increasingly clear. We expect the following three trends to accelerate and intensify in 2022.

Trend #1: The rise of the just-in-time data analytics stack

There is a small but rapidly growing segment of the data analytics space that is focused on new approaches to the business stack. Of course, these new approaches also include continuing to move everything to the cloud. That’s not new. What is new, however, is the awareness that there is no single cloud and that hybrid multiclouds have their own requirements. Perhaps the most important requirement is the ability to manage and analyze data regardless of its location in the hybrid multicloud environment.Everything is moving towards hybrid multicloud, which means that a new approach to data analytics – including integration, search, query, AI / ML, and even reporting – results in your data being less critical and less shocking than it means.

There are at least 10 startups building platforms to query, search, connect, analyze and integrate data where it is without just moving or copying it just in time. These startups range from traditional OLAP data cube analysis in a data warehouse to search. and NoSQL data storage, as well as data structure and knowledge graphing methods for integrating and connecting data.

In a world where the number of locations where data is stored is increasing rather than decreasing, organizations will look for data analytics solutions that are not tied to the location of the data.

The value of data-driven decision making and analytics is critical to competitiveness in the knowledge economy, which means enterprise software vendors are rushing to see who can cut down on time and the cost of generating information using corporate data. This trend will accelerate in 2022, as the movement of data between storage systems occurs at a reduced rate and is less central in the data stack to speed up time to insight.

Trend #2: The era of big data centralization and consolidation is over

Linked to the previous trend of both accelerating and accelerating is the lesser importance of centralized or consolidated data storage. To be clear, this trend is not the end of the storage. There will never be an end to storage. Rather, this trend marks the end of centrally consolidated approaches to data warehousing, especially for analytics and application development.

In 2022 we will see the continuation of the great struggle that is brewing in the field of data analytics as old forms of corporate data management that focus on patterns of consolidation and centralization peak and then begin to prevail. Seeing how it unfolds in the great battle between Snowflake and Databricks in 2022 and beyond is a function of their different approaches to centralized consolidation. Snowflake exemplifies the conventional approach with 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. However, Databricks presents a more decentralized and compute-intensive approach because of its tradition as an Apache Spark company. Other providers are even more demanding, deepens the need for centralized data consolidation before it can be managed, as in trend # 1.

It’s not just about technical pressure. The economics of the inevitable movement of data in a hybrid multi-cloud world is not good and does not seem to be improving. Customers and investors reject the lockdown that comes with centralization approaches. Something has to give of this battle and we expect the pendulum to swing in the direction of decentralization and disintermediation of the data analytics stack.

Trend #3: Data fabric goes mainstream

According to analysts, data fabric is the future of data management, but when will that future come and when will it be evenly distributed? The third trend that we expect in 2022 is that the corporate data structure as the key to data integration in the hybrid multicloud world will achieve a clearer business maturity. Among the many signs, we will see increasing analyst attention on this growing portion of the data analysis stack, including real-world case studies and fully addressable market forecasts.

The coming year will also bring high profile business adoption that will include use cases like modernizing analytics, accelerating data lake insights, digital twins in manufacturing and supply chain, and drug discovery and supply chain control in the pharmaceutical industry and industry Life sciences.

It is perhaps ironic that all data innovation has been focused in the last 20 years, some might say that it has focused too much on the analytical components of the stack, and those are certainly critical components.

However, just as race cars without high octane fuel sources are just fine static sculptures, analytics platforms such as AI / ML without full data control, accessibility and innovative solutions data integration will fail to harness their potential. Numerous market signals suggest that by 2022, the company itself will take seriously the search for new ways to integrate and connect data in the new hybrid multicloud world we live in.

Closing Thoughts

These three trends are different, but they are also related. Due to the pandemic and the challenges associated with it, we have experienced many exogenous shocks for the “making sense” of the global business machinery. This has accelerated the awareness that the world has changed rapidly and we are living in a new hybrid multi-cloud reality. This shift, which has centered on the lower levels of the IT stack – that is, data centers, networks, raw storage, and compute resources – is now spreading, affecting both the way we analyze and integrate the data Accelerate this change in 2022.

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