Consolidate your data marts for fast, flexible analytics

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To expand the reach of data and analytics to business users, many organizations leveraged data marts to address specific department or user needs. However, this has led to a proliferation of siloed data across these organizations, resulting in a new set of inefficiencies and self-service challenges.

In addition, the purpose-built appliances used to build these data marts require upfront modeling, and have costly scale and access limitations. This, in turn, impairs the agility of the organization. With some of these appliances facing end of life, it’s an ideal opportunity for enterprises to modernize their architecture.

In the modern era, organizations must adopt analytic strategies to:

  • Consolidate data silos for faster, easier analytics and simplified operations.
  • Architect the data to support both existing reports and analytics
  • Enable self-service BI and discovery, using the business users existing skill set
  • Deliver the performance expected from legacy appliances, across more users and use cases.
  • Go beyond SQL to support data science, operational applications.
  • Build a platform for shared data, including shared metadata, security, and governance.

To expand the reach of data and analytics to business users, many organizations leveraged data marts to address specific department or user needs. However, this has led to a proliferation of siloed data across these organizations, resulting in a new set of inefficiencies and self-service challenges.

In addition, the purpose-built appliances used to build these data marts require upfront modeling, and have costly scale and access limitations. This, in turn, impairs the agility of the organization. With some of these appliances facing end of life, it’s an ideal opportunity for enterprises to modernize their architecture.

In the modern era, organizations must adopt analytic strategies to:

  • Consolidate data silos for faster, easier analytics and simplified operations.
  • Architect the data to support both existing reports and analytics
  • Enable self-service BI and discovery, using the business users existing skill set
  • Deliver the performance expected from legacy appliances, across more users and use cases.
  • Go beyond SQL to support data science, operational applications.
  • Build a platform for shared data, including shared metadata, security, and governance.

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Featured speakers

Alex Gutow

Director, Product Marketing at Cloudera

Alex Gutow is the director of product marketing at Cloudera, where she focuses on the analytic database platform solution and technologies. Previously, she managed technical marketing and PR for Basho Technologies and managed consumer and enterprise marketing for Truaxis, a Mastercard company. Alex holds a BS in marketing and a BA in psychology from Carnegie Mellon University.

Josh Klahr

VP of Product at AtScale

Josh majored in Ferrous Metallurgy (yeah...look it up) as an undergraduate at Brown University, envisioning a long career in the steel industry. After realizing that the steel industry was going soft, he went on to pursue a career in the more lucrative world of data and analytics after receiving his MBA from Stanford. Josh spends his working day torturing the AtScale engineering team by starting sentences with, “Wouldn’t it be cool if...?” In his spare time he divides his time evenly between cooking for his wife and two kids, golfing, playing basketball, and drinking a ridiculous amount of Peet’s coffee.

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