Data Landscape Assessment: Analytics CEO Reveals Key Trends
Solutions Review’s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, Starburst CEO Justin Borgman offers his take on the most important trends to know when making a data landscape assessment for your organization.
2022 was the year that companies embraced multi-cloud, unleashing a whole new set of challenges associated with different cloud vendors and creating complications for companies looking to mature and scale after the pandemic.
Looking ahead into 2023, here are four key trends in the data landscape that will shape how organizations do business in the upcoming year.
Data Landscape Assessment
CIOs Need to Become Vigilant About Spending Data Dollars Efficiently
We’re all seeing pressure on IT budgets, and data spending is not immune. The cloud data analytics space has greatly evolved over the past decade, as have business leader priorities. As the industry continues to rapidly grow and economic pressures continue to mount, CIOs and CDOs are starting to work together to drive efficiency into data management & analytics. We see three common cost savings measures: (1) Companies are reducing data stored in expensive data warehouses and opting to place more of their data in a lake. (2) Some cloud migration projects have been deferred as cost control of data in the cloud has been a challenge, (3) Costs and inefficiencies related to data movement and copy management are being significantly reduced as companies are opting to leave the data where it lives.
Analysts Will Want to do Analytics in their Own House
2022 brought heated debate around data warehouses versus data lakehouses and why one over the other serves as the logical solution for storing, analyzing, and securing large amounts of data. Ultimately I predict that in 2023, this debate will stall as companies will want to analyze all of the data in their house, and there is no one-size-fits-all centralized architecture. To get the most out of their data, they’re going to need to make it all available for analytics, and that requires a distributed data architecture over-focusing on one approach over the other.
The Data Democratization & Data Governance Balancing Act Takes Center Stage
The trend of data democratization will continue to grow as organizations increasingly seek greater accessibility. However, data democratization comes with risks, and today’s organizations are faced with a challenge — how do you drive governance around data democratization?
With the continued rise of data democratization, we’ll see a shift from a storage-centric world to an analytics-centric world, one where data is treated as a first-class product to be consumed by the rest of the organization. The democratization of Data Products enables organizations to have greater access to their data across the board, but with that, there also needs to be fine-grained access controls. To support that, similar to how the data science occupation was created about 10 years ago to support big data analytics projects, in 2023 we’ll see the Data Product Manager role emerge to provide the necessary governance to facilitate who has access to what.
There Will be a Consolidation of the Vendors Supplying Small Parts of the Modern Data Stack
The modern data stack has had its day, but the rose-colored glasses have come off – folks realize cloud doesn’t necessarily mean modern and are transitioning their focus to the post-modern data stack. The post-modern data stack takes elements of cloud efficiency and agility and faster access to data – but focuses on having a unified architecture that supports accessing distributed data. Data centralization is not modern, and today’s definition of the modern data stack still supports moving much or all of your data to a central location before analyzing it. As more companies lean into creating a distributed data architecture, we’ll see consolidation among the vendors that are only addressing small pieces of the centralized modern data stack.
We’ve reached a breaking point in the data & analytics space and major paradigm shifts are on the horizon. In 2023, fluttering IT budgets, decentralized data, data democratization, and vendor consolidation will be key trends reshaping the data landscape as we move into the post-modern data stack era.
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