The Data Virtualization Gold Standard

Robert Eve

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Data Discovery + Data Virtualization = Better BI

Accelerate BI time to solution and improve BI solution quality

It has been said that the ability to see patterns is a sign of intelligence.

Certainly the goal of business intelligence (BI) solutions is to provide some level of intelligence or insight from the patterns of data these tools analyze.

But can these BI applications figure out the patterns hidden in a typical enterprise's data schemas and structures?

They cannot!

That is why humans must intervene and build data models that rationalize diverse sources into consistent structures that BI can use.

What If We Could?

  • What if we can give these BI tools a boost by automatically revealing valuable relationships among sources data so they could be more easily surfaced to business users?
  • What if we could help data modelers and developers better understand the data so they could accelerate development of these valuable information applications?
  • What if we could automatically alert both business and IT when new data relationships arose or existing ones changed so they could promptly respond to this new opportunity?

Data Discovery Plus Data Virtualization Turns "What If" into Reality
Data discovery is a solution that helps IT see patterns amongst diverse source data.  It enables IT analysts and architects to examine data, locate key entities and reveal hidden connections in data scattered throughout an organization.

They can use that knowledge to quickly create and implement the rationalized schemas BI tools require using data virtualization platforms. These rapidly built schemas make it easier to validate and test business requirements with end users early in the BI solution development process, improving both time to solution and solution quality.

Taking Time out of Time to Solution
A well-known obstacle to BI solution development is the long cycles it take to get the requirements right.  A slow development and validation process creates confusion as IT and business users get out of synch on what they need to accomplish.  Data discovery, combined with data virtualization, lets IT and business professionals simplify and accelerate the requirements gathering and data validation process; speeding time to solution.

Greater Accuracy, with Fewer Iterations
Data discovery helps align data's business and technical contexts, facilitating greater collaboration between business and IT professionals.  Discovery's ability to display meta-data in an easy-to-read format allows users to easily validate requirements with greater confidence.  More accurate validation at the front-end of the project reduces corrective actions in downstream steps; ensuring that end BI solution meets business objectives.

Fewer Experts Required
Discovery's ease-of-use and automation reduces the need for data modeling expertise.  Project team members can now redirect these efforts toward development of additional BI applications.

Checklist of Key Capabilities
Data discovery combined with data virtualization can simplify the upfront data modeling process to accelerate and improve your business intelligence projects.  To do this well requires:

  • Uncover Data Sources - Locate relevant entities across the multiple data silos typical in enterprise IT today.
  • Discover Relationships - Reveal data relationships across disparate entities using formal keys and fuzzy matching. This provides greater insight into a complex data environment to accelerate data modeling.
  • High Productivity Data Modeling - Shape and refine data models in a rich graphical environment, enabling simple and flexible data modeling.
  • Pragmatic, Bottom-up Data Modeling - Build models from the ground up with metadata tied to actual data sources.
  • Easy-to-use Design Functions - Automate a variety of design activities including transformation, filtering, parameter passing and more.
  • Automated SQL Development - Automatically generate SQL code using simple menu selection methods, without needing to know SQL.
  • Adaptable Rules Engine - Provide hints to the relationship discovery process to improve matching accuracy.
  • Data Virtualization Platform Integration - Transfer models from the discovery tool to the data virtualization platform with one click, enabling fast and seamless deployment.

More Stories By Robert Eve

Robert Eve is the EVP of Marketing at Composite Software, the data virtualization gold standard and co-author of Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility. Bob's experience includes executive level roles at leading enterprise software companies such as Mercury Interactive, PeopleSoft, and Oracle. Bob holds a Masters of Science from the Massachusetts Institute of Technology and a Bachelor of Science from the University of California at Berkeley.