Democratizing Data Access, Analytics and Innovation on the Cloud Data Platform

  • Kevin PetrieEckerson Group
  • Ben HudsonStaff Product Manager, Dremio

Session Abstract

Digital transformation, data democratization, and cloud modernization are fueling the rise of cloud data platforms. By running SQL workloads directly on cloud-native object storage, the cloud data platform seeks to merge the best of data warehouse and data lake technologies. Enterprise BI analysts and data scientists alike consume data from these repositories to answer their growing analytics needs.That’s why enterprises adopt cloud data platforms. But how do their data teams actually achieve those goals? They face obstacles such as complex data warehouse structures, slow performance, and siloed datasets. Data engineers in particular struggle to simplify, accelerate, and consolidate analytics workloads on cloud data platforms. This webinar provides guiding principles to overcome the obstacles.Join Eckerson Group and Dremio to learn how your data team can:

  • Open up data access for decision makers throughout the enterprise
  • Reduce the need for complex BI extracts, aggregation tables, and OLAP cubes
  • Improve latency and throughput for analytics
  • Eliminate data silos
  • Foster innovation with open data formats, APIs, and ecosystem support

Ready to Get Started? Here Are Some Resources to Help

Analyst Report

The Establishment and Utilization of Data Lakes

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The Forrester Total Economic Impact of the Dremio Lakehouse Platform

The Total Economic Impact™ (TEI) study by Forrester Consulting shows how five Dremio customers leveraged the Dremio lakehouse platform and realized significant quantitative benefits in data scientist, business analyst, and data engineering productivity as well as significant data storage cost savings.

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