A new independent survey by AtScale, the intelligent data virtualization provider for advanced analytics, in collaboration with Cloudera and ODPi, a Linux Foundation Project, reveals that 79% of enterprises want better integrated security and governance for their data in the cloud. You can download the full “Big Data & Analytics Maturity 2020 Survey Report” here.
The survey results also reveal that data virtualization and data governance are top priorities for big data and analytics leaders. Key findings from the survey include:
The Majority (79%) of Enterprises Use Multi-Cloud or Hybrid Cloud Strategies – Only 24% of those surveyed they are all in with a single cloud vendor.
Companies Are Implementing Data Virtualization – More than half (55%) of respondents plan to invest in data virtualization in the near future if they are not already.
Data Governance Is a Top Challenge Across the Board – 80% of respondents said that data governance is very important to them.
Dave Mariani, chief strategy officer and founder, AtScale shared these insights on the survey's findings:
What surprised you most about this survey's findings?
A few things stood out for me in the survey that I wasn’t anticipating.
First, while it’s clear that Hadoop has failed to be the panacea for all things data warehousing, Hadoop is still a growing presence in the enterprise. This makes sense coupled with other responses in the survey that suggest that IT is living in a hybrid world where they are choosing the best tool for the workload versus a “one size fits all” approach.
Second, it’s clear that data governance is top of mind for just about all of the respondents. I think these responses are indicative of the anxiety created for IT in a multi-site, multi-platform world where just one slip up in data security and governance means losing your job.
Third, it’s abundantly clear that enterprises are moving away from a data movement centric, hub and spoke ETL heavy, data integration strategy. We see this in the numbers in the drop of anticipated future investment in ETL and the growth in anticipated future investment in Data Virtualization.
How should companies change their security and governance approaches in multi-cloud or hybrid cloud environments?
For data governance to date, there’s been a big focus on data cataloging tools. These tools are great for letting you know that you have a big, hairy problem, but they typically don’t help you out of your predicament. In a hybrid world full of purpose-built data platforms and wild west data lakes, it’s imperative that enterprises invest in data governance enforcement tools, not just policy management and cataloging tools. In other words, they should develop a strategy where every query, regardless of where it originates and where it’s going applies the same filters and access rules consistently across the enterprise.
What are the benefits of data virtualization? How can data virtualization help in the multi/hybrid cloud?
Data Virtualization (DV) helps enterprises get control of their data assets in some critical ways. First, as a universal semantic layer, DV hides the physical implementation of the data while presenting a unified view of that data to any tool or application. That means everyone is speaking the same (semantic) language. Second, DV is a great “man in the middle” approach to enforcing data governance and security consistently across the enterprise. Essentially, DV inspects every query creating a central audit trail and enforcement layer. Finally, DV is a great tool for helping enterprises migrate their data assets to the cloud without a “rip and replace” strategy that is risky and disrupts downstream data consumers. By hiding the physical location of the data, DV provides IT with the aircover to migrate data to new clouds and/or platforms without end users even knowing about it.
What sets AtScale apart from other data virtualization offerings
AtScale is an Intelligent Data Virtualization platform. What doesn’t “intelligent” mean? AtScale didn’t set out to be a data federation layer. We set out to create an OLAP powered, business intelligence engine that is built for today’s data types, tools and massive data scale. OLAP is critical to business since it provides (1) computational power critical for the business, (2) a universal semantic layer and (3) “speed-of-thought” queries. It’s what business users demand. We added query federation because our customers asked us for the ability to create virtual cubes that spanned multiple data sources. It was a natural extension and since we had already solved the scale out problem without Intelligent Aggregates, we were able to make query federation work at scale while legacy DV vendors are still relegated to small data and simple use cases.