Drawing the Big Picture: Multi-Platform Data Architectures, Queries, and Analytics

TDWI Speaker: Philip Russom, TDWI Research Director

Date: Wednesday, August 26, 2015

Time: 9:00 a.m. PT, 12:00 p.m. ET

Webinar Abstract

If you’re truly passionate about data, you want to reach as much data as possible, no matter where it comes from, where it resides, what type of platform it’s on, or what structure it’s in. That’s because the mission of the data management professional is to integrate data creatively and comprehensively to serve an evolving array of business purposes.

The mission is noble, but it faces many challenges. Given the complexity of today’s multi-platform data ecosystems, it’s difficult to draw a big picture of the available datasets, plus relationships among them and flows across them. Pulling all that together into a functional architecture is likewise challenging.

To help you draw the big picture of diverse data, this Webinar will discuss:

  • Modern data warehouse environments (DWEs), which consist of many diverse types of data platforms capable of storing and processing many types of data with equally diverse workloads for queries, analytics, data integration, and so on.
  • Single-console tools, which address complexity by presenting a unified view of disparate data and by enabling the development and execution of multi-platform solutions.
  • Positive ramifications of the unified big picture of data.Besides enabling new ways to view data and develop queries and analytics, the big picture also simplifies data architecture, governance, stewardship, security, compliance, and auditing.
  • Data exploration, which is very important for user organizations that are seeking business value from big data, as well as for the growing number of data analysts who explore data on multiple platforms as a prelude to a unified analytic result.
  • Standard SQL, which must be a prominent piece in any multi-platform, data-driven solution, because so many users wish to leverage their SQL skills and portfolios of SQL-based tools. The challenge is to make new, diverse data SQL-addressable, even when it’s schema free and on non-relational platforms.

Philip Russom, Ph.D.

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