3 Ways Data Management Drives AI Initiatives

IDC is expecting data to grow 61% yearly to reach 175 zettabytes worldwide in 2025. While many organizations recognize the opportunity this explosion of data brings, most are not ready for the data ingestion and preparation demands needed to transform their businesses.

With this, there needs to be a paradigm shift in how data is managed and accessed to drive AI application development and achieve competitive advantages. This involves self-learning, automated data management powered by AI as well as tools enabling AI development initiatives within the data management architecture.

Watch the ET Unwired Session and hear from our experts as they discuss the concept of an AI database, and how data management with embedded AI capabilities enables:

  • Operational efficiency with autonomous database capabilities and machine learning query optimization
  • Systematic innovation that allows for AI models to be deployed via natural language querying and SQL
  • Improved data science with data virtualization, sampling de-biasing, and data cleansing

Speakers

Mike Gualtieri
Vice President, Principal Analyst
Forrester

Sam Lightstone
CTO – AI Strategy, IBM Master Inventor
IBM

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Mike’s research focuses on artificial intelligence (AI) technologies, platforms, and practices that enable technology professionals to deliver digital transformations that lead to prescient digital experiences and breakthrough operational efficiency.
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I am the CTO for data products in Analytics Platform. This includes our database products for noSQL, SQL, Big Data, data warehousing, data virtualization. This work encompasses multiple platforms including public cloud, private cloud, IoT, appliance, and traditional software.

I joined the Academy of Technology in 2010. I served on the IBM Academy Leadership Team 2015-2018. I’m lucky to also be an IBM Fellow and an IBM Master Inventor.

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