Industry executives and experts share their predictions for 2023. Read them in this 15th annual VMblog.com series exclusive.
The Year of Data Architecture and Predictive Analytics
By members of the Databricks team
We are in a world where companies are collecting more data than ever before. It’s how they organize and analyze that data to make business decisions that will count in 2023 and beyond.
Growing companies across industries – from media and entertainment to healthcare to public sector – are prioritizing data science and data analytics, and working to eliminate data silos to make their data more intelligent.
Running AI and storing data is extremely costly and reevaluating that spend will be top of mind for companies in 2023. From attracting and retaining IT talent to pruning their tech platforms, companies will all be doing what they can to simplify their data architecture to drive digital transformation in the years ahead.
Read on to see more predictions from leaders at Databricks:
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David Meyer, SVP of Product Management, Databricks
The data platform will emerge as the central driver of multi-cloud strategy.
“Whether happenstance or intentional, most enterprises are multi-cloud today. As enterprises consolidate all of their data-oriented use cases on a data lakehouse, they will prioritize their cloud vendor decisions based on data workload needs including ease of use, performance, regulatory compliance, and unified management across clouds.”
AI will rescue cloud customers from their ballooning costs.
“Enterprises have rushed into the cloud, unleashing productivity but also leading to sprawl that has ballooned costs. In an increasingly uncertain macro environment, AI will come to the rescue and reduce costs by understanding customers’ workloads over time and automatically right-sizing their deployments for optimal cost and productivity tradeoffs.”
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Naveen Zutshi, CIO, Databricks
CIOs Will Look to Consolidate Data and Simplify Architecture.
“Speaking with other CIOs, I’ve noticed that companies are growing exponentially without a plan to organize their data. When a company considers scaling at all costs but doesn’t invest in the right technology to support that growth, there will be issues. Part of the problem is that CIOs today have to manage too many systems. Too many disjointed data pools lead to duplicated, siloed, and locked-up data, which is not only timely and costly to manage and analyze but also leads to security issues. For a company to truly move forward with digital transformation, they need to combine data science and data analytics and draw from a single source of truth. We’ll see more CIOs cutting back on vendor spending to simplify their data architecture. Companies that implement an architecture that combines hindsight and predictive analytics to deliver efficient and intelligent solutions will win in the end.”
IT Will Expand Hiring Criteria.
“Finding and retaining high-caliber IT talent has been a challenge this past year. I foresee a softening of the IT market as companies look to grow more prudently in 2023. As part of that, companies will need to look at hiring differently. I think we’ll see companies hire more employees early in their careers and also look to expand things like internships and year-end programs to support that. With remote work here to stay, organizations will continue to look for talent across geographies and from less traditional backgrounds. As a result, we’ll see companies invest in robust training and development programs to better train employees who may not have the deepest technical expertise.”
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Fermín J. Serna, Chief Security Officer, Databricks
The rise of the data lakehouse will lead to simplicity but will require a rethinking of data security and governance.
“Enterprises will increasingly migrate to the data lakehouse, which is a unified data platform for previously siloed workloads such as data engineering, warehousing, streaming, data science, and machine learning. Unifying these silos unlocks tremendous value for businesses, but also requires the organization to evolve to realize the full potential of the platform. Understanding that data remains one of the most valued assets within a business; forward-thinking enterprises will also be looking for simplicity by consolidating on a single vendor lakehouse architecture. Enterprises will evolve their teams and processes to adopt a secure, centralized management and governance model with the associated tooling for the data assets that span multiple workloads.”
Organizations will adopt secure data sharing based on open standards, avoiding vendor lock-in.
“The value and importance of enterprise data have kept it under heavy lock and key, but this has also limited the velocity of innovation because businesses don’t have adequate means to confidently share their data both internally within the organization and externally with other organizations. However, advances in secure data-sharing standards based on open-source change the equation because enterprises now have a way of securely sharing their data while avoiding the pitfalls of opacity and getting locked into a particular vendor. Entering 2023, we will see an uptick in ‘secure sharing,’ the idea and ability to share data internally and externally while centrally governing its access and without duplicating the data.”
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As more and more companies look to analyze vast amounts of data using AI and ML, they will need to consider their data architecture. With data organization and open data-sharing come several benefits such as working from a secure, centralized data source, simplifying workloads, and harnessing predictive analytics.
