Gartner Data and Analytics Summit in Grapevine, Texas

March 5 - 8, 2018

Coming to the Gartner Data and Analytics Summit?

Come say "Hi" to us at Booth #1015 at the Gartner Data and Analytics Summit, where you'll learn about the latest on advanced analytics, big data and business intelligence technologies you need to generate new revenue.

Here are some highlights from the Gartner Data and Analytics Summit 2018 schedule:

  • Meet with our team. Whether you are ready to kick off a visual analytics project or have technical questions for our engineers, swing by our booth or request a meeting in advance.
  • Data Lakes vs. Data Warehouses Learn the pros and cons of each architecture and why existing BI tools are structured well for data warehouses, but not data lakes.
  • Can’t make it to Gartner this time? Download Arcadia Instant and maybe you’ll be speaking on behalf of Arcadia Data at Gartner next year!

Let us know what day you want to meet and we will contact you to set up a convenient time:

Don't miss out on this talk from Randy Lea, our Chief Solutions Officer


Randy Lea

Chief Solutions Officer
Arcadia Data

A Tale of Two BI Standards: Data Warehouses and Data Lakes

9:45am–10:15am Thursday, March 8, 2018

Data lakes as part of the logical data warehouse (LDW) have entered the trough of disillusionment. Some failures are due to lack of value from businesses focusing on the big “data” challenges and not the big “analytics” opportunity. Data is just data until you analyze it.

While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives?

In this talk, we’ll discuss:

  • Why existing BI tools are architected well for data warehouses, but not data lakes.
  • The pros and cons of each architecture.
  • Why every organization should have two BI standards: one for data warehouses and one for data lakes.

Can't make it this year?

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