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The trend has been clear for some time: Data is changing, the script is flipping and the intelligent data platform is rising.<\/span>\u00a0Generative artificial intelligence is set to change the data layer completely.<\/p>\n The ongoing platform shift was a central focus of the Supercloud 7: Get Ready for the Next Data Platform event<\/a>, which ran from July 30 to 31. According to John Furrier (pictured), executive analyst for theCUBE Research, the platform shift absolutely targets what will happen next as infrastructure improves.<\/p>\n Rob Strechay, John Furrier, Savannah Peterson and Dave Vellante talk about the intelligent data platform during Supercloud 7.<\/p>\n<\/div>\n \u201cAs infrastructure closes the loop and gets stronger, the data layer is going to change very rapidly,\u201d Furrier said during Supercloud 7. \u201cThe data\u2019s clear that this is evidently happening right now in the market.\u201d<\/p>\n The opportunities for innovation and many other subjects were explored by Furrier, Dave Vellante<\/a>, chief analyst at theCUBE Research, and a full team of analysts at theCUBE Research. They discussed the future of AI infrastructure and the rise of the intelligent data platform.<\/p>\n Here are three key insights you may have missed from Supercloud 7:<\/p>\n Supercloud 7 included a discussion of Enterprise Technology Research survey results recently published by SiliconANGLE involving more than 100 joint Databricks Inc. and Snowflake Inc. accounts. The results suggested that enterprise customers are conflicted about the best route possible when it comes to balancing data trust with a desire to move fast and innovate amid the rise of the intelligent data platform.<\/p>\n When asked about their preferences for open table formats, most ranked security and governance and lock-in avoidance first and second. But there\u2019s a \u201cswing vote\u201d at play here, according to Vellante.<\/p>\n George Gilbert Research talks about ETR survey results during Supercloud 7.<\/p>\n<\/div>\n \u201cThere\u2019s 14% that said data security is less important than creating a stack that allows for rapid innovation. Why is that the swing vote?\u201d he asked. \u201cIt\u2019s because ETR correlated that and found it. Those were the ones that were most likely to [leave] Snowflake and move to Databricks as an example, because they\u2019re saying \u2018damn the torpedoes\u2019 in governance.\u201d<\/p>\n When one starts talking about open table formats, they must essentially start abstracting governance from the purview of any one vendor, according to theCUBE Research\u2019s George Gilbert<\/a>. That means thinking about governing all of the data in one\u2019s data and application estate.<\/p>\n \u201cSnowflake\u2019s appeal was, \u2018Hey, we\u2019ll take care of governance. You bring whatever tool you want, go through our engine, and it\u2019s all seamless.\u2019 And then they were like, \u2018We\u2019ll extend that to all Iceberg tables, and we\u2019ll synchronize governance to the Polaris catalog,\u2019\u201d Gilbert said. \u201cYou have governance across your Snowflake data and your open Iceberg data.\u201d<\/p>\n Meanwhile, Rohan Kumar<\/a>, corporate vice president of Azure Data at Microsoft Corp., has suggested that its Microsoft Purview Data Governance<\/a> solution would see users set policy and tag all data \u2014 not only across Azure data, but across clouds, on-prem, and edge. Microsoft would author the policies, and users would set the tags.<\/p>\n \u201cNo one governance rules them all is really the message there,\u201d Vellante said.<\/p>\n As database vendors navigate the shifting landscape of compute engines for AI, theCUBE analysts see changes ahead. Table formats have changed the game, according to Sanjeev Mohan<\/a>, principal at SanjMo and analyst for theCUBE Collective.<\/p>\n \u201cIf I can build reports and dashboards very easily in Snowflake with an amazing user experience, great. But if I want to do AI and machine learning, maybe I should use Databricks,\u201d he said. \u201cIf I want to do my data cleansing and data prep, I should use Apache Spark. It\u2019s not making copies of the data and moving it around, but it\u2019s changing the compute engine.\u201d<\/p>\n Amid the rise of the intelligent data platform, companies are making a concerted effort to enhance scalability, flexibility and security. That plays out in several ways, including for the multinational retail corporation Walmart Inc.<\/p>\n The retail giant has sought to utilize large language models for online and physical commerce. The company\u2019s machine learning platform, Element, has changed the game for its cloud operations, according to Anil Madan<\/a>, senior vice president of cloud and data platforms at Walmart Global Tech.<\/p>\n Microsoft\u2019s Dipti Borkar talks about the future of data platforms.<\/p>\n<\/div>\n \u201cWe manage from a data life cycle, thousands and thousands of data sources. The data lifecycle is data moving in more in a raw format, coming into a central lake. It goes through certain transformations and quality to create a data catalog,\u201d Madan said. \u201cThat data catalog helps very much power every aspect of our analytics and machine learning.\u201d<\/p>\n Meanwhile, Databricks has also sought to advance the evolution of data platforms by emphasizing the use of open formats and AI integration, with an eye on driving efficiency in data management. When it comes to future-proofing data platforms, open formats and interoperability between different data engines are crucial, according to Ali Ghodsi<\/a>, co-founder and chief executive officer of Databricks.<\/p>\n \u201c[Customers are] super excited to see interoperability between these formats,\u201d he said. \u201cThey don\u2019t want to see incompatibility between Delta Lake and Iceberg. The fact we\u2019re unifying them in project UniForm, and now you can get both of those and you get full compatibility of your data, they loved it.\u201d<\/p>\n Microsoft also has its eyes on advancing the future of data platforms as it shifts to pure open formats, with Microsoft Fabric<\/a> in particular. It represented a dramatic change for the company, according to Dipti Borkar<\/a>, vice president and general manager at Microsoft.<\/p>\n \u201c[We moved] all our engines to reengineer these computes, to now read these native formats,\u201d Borkar said. \u201cWe support Delta Lake, and Iceberg is landing very soon. The reason that these are important, again, customers get a choice.\u201d<\/p>\n Among many key insights at Supercloud 7, it quickly became clear that the evolving landscape around the intelligent data platform includes a focus on the adoption of open standards and seamless interoperability. Snowflake, for instance, has sought to balance solutions integration with the adoption of open standards.<\/p>\n Snowflake, of course, has made Polaris open source. The company\u2019s goal is to commit to open-source principles and enhance its products through collaboration, according to Benoit Dageville<\/a>, co-founder and president of product at Snowflake.<\/p>\n Snowflake\u2019s Benoit Dageville talks open-source principles during Supercloud 7.<\/p>\n<\/div>\n \u201cOur customers, or a class of our customers, is asking us for interoperability between tools,\u201d Dageville said. \u201cMany tools are accessing the same data, and they want Snowflake to be one of these tools or one of the systems accessing this open data. They ask us to come to their data versus their data coming to us, and they want to avoid vendor lock-in.\u201d<\/p>\n Vast Data Inc., meanwhile, has aimed to create a unified data pipeline that integrates multiple clouds and data centers. That allows companies the ability to federate multiple clouds with the Vast DataSpace, according to Jeff Denworth<\/a>, co-founder of Vast Data.<\/p>\n \u201cEssentially, it allows you to kind of flow all your files and all of your records that sit in tables across a series of independent cloud platforms so that you can have one unified pipeline,\u201d Denworth said.<\/p>\n For some companies, there\u2019s been a shift toward platform-centric models. TransUnion LLC has sought to embrace that new shift given its tens of thousands of daily data sets and more than 50 billion data points, according to Venkat Achanta<\/a>, chief technology, data and analytics officer at TransUnion.<\/p>\n \u201cWe curate that data, the data quality, cataloging of the data, more importantly connecting that data we call identity resolution, trying to figure out where this food this data belongs to and then serving up that data into intelligent predictive applications and cognitive applications for banks and the consumers to consume,\u201d Achanta said.<\/p>\n Stay tuned for the complete video playlist, part of SiliconANGLE\u2019s and theCUBE Research\u2019s coverage of the Supercloud 7: Get Ready for the Next Data Platform event.<\/p>\n1. Enterprise customers are conflicted on data governance.<\/h3>\n
2. Companies are seeking to respond to the intelligent data platform.<\/h3>\n
3. There\u2019s an effort to enhance data platforms with open standards and interoperability.<\/h3>\n
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