Data Modeling Tools Use Visualization Techniques

by   |   April 9, 2013 12:13 pm   |   0 Comments

 Visualization in data governance helps illustrate the data value chain – including data provenance – so that business and technical decision makers can enhance processes and improve productivity.

Embarcadero’s ER Studio data modeling tool visualizes the data value chain at a financial institution. Visualization in data governance helps illustrate the data value chain – including data provenance – so that decision makers can enhance business processes.

Unprecedented data growth, compliance and regulatory challenges and the need for speed in business has made the role of data governance ever more critical.

On one hand, a proliferation of regulations and standards creates challenges for data governance, especially when multiple regulations seem to overlap. For example, regulations such as Sarbanes-Oxley try to enforce a balance between information access and appropriate use of information that needs to be considered in data governance policies. Then, on the other hand, corporate performance often hinges on having the right data at the right time – late data or incorrect data can wreak havoc.

An industry of sorts has grown up around this problem, with some data modeling tools vendors approaching it from perspectives that can include data quality, master data management (MDM), and regulatory compliance.

For example, CA describes its ERwin data modeling product as providing both business and technical stakeholders “a centralized view of key data definitions” through a collaborative data modeling environment.

The diversity of approaches has meant that it often remains difficult for an IT decision maker to get a clear view of the whole governance picture. That was true even before the trends of cloud and mobile computing hit the scene. “Cloud and mobility introduce additional security concerns into the data governance picture. Big data does too but very few vendors, and not many users, are really paying much attention to data governance for big data yet,” Philip Howard, an analyst at Bloor Research, said via e-mail.

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Those issues and the absence of a global view of governance have spurred vendors to try to come up with a solution. Embarcadero’s metadata governance strategy is an example. The company’s products serves as a starting point for data governance by trying to provide a comprehensive picture of all data assets, no matter what form they take or where they are located.

Henry Olson, director of product management at Embarcadero Technologies, says Embarcadero has been focused just on information management for most of its 20-year history. He says the company has found that many of its customers are currently considering a data governance initiative or actively implementing one, providing particular relevance for the product.

However, he notes, there is often a big gap between the policies, procedures and initiatives regarding governance that originate with management and the actual day-to-day  activities of IT people simply trying to get things done. “We believe we have a role to play in bridging that gap so everyone works on the same page. The way we do it is to provide enterprise information and a comprehensive inventory of assets,” he says. Olson says companies spend tens of millions of dollar putting their elaborate IT systems together. Embarcadero provides tools to optimize those investments and help them deliver value.

One of the ways Embarcadero does that is through greater visualization.  “We map the territory; we are effectively inventorying all the enterprise information and classify it in terms of meaning and business relevance,” he explains. That process helps companies coordinate resources and reveal the meaning of data. “In doing so we can understand where the gaps are and the risks and issues and how best to use the information you have,” he says.

What this all means in a business context is illustrated by an application of the technology at a large investment bank. “They had to put together trading algorithms but in order to do so they needed to understand the meaning – the provenance – of the data they were using,” he explains. If the company didn’t “have it right” – for example if the data was stale — then they wouldn’t be executing the right trades.  The Embarcadero approach helped “get the metadata off the shelf and provide it to people for their day-to-day tasks,” he says. One element of that are the mapping capabilities in Embarcadero’s tool, he explains.

Howard noted that while ER/Studio addresses metadata governance and associated issues that form a part of data governance, metadata is not the whole story of data governance. When most people talk about data governance, he notes, they tend to include issues such as data quality and MDM in addition to the metadata aspects of data governance.

The capabilities of a tool like Embarcadero’s are still valuable, though. “Visualization is important – especially as it enables business users to understand what’s going on so that they can collaborate better with data stewards,” Howard said.

Data governance specifically for CRM/ERP solutions remains challenging, he notes. “They may have data quality elements built into them but as far as metadata is concerned you need some sort of tool (for example, Safyr from Silwood Technologies) to extract the metadata that represents the customization that most users have done,” noted Howard.

“The point about Safyr is that it allows you to visualize the structure of an ERP or CRM environment, including all the customizations therein, and then load that into a data modeling tool,” he says. This is important because a lot of the rules about data, especially in an ERP environment like SAP, are defined within the application rather than the database, Howard added. So the data modeling tool is an enabler for other technologies.

From Embarcadero’s perspective, the point of the company’s tools are to enable stronger data governance, Olsen says, because they enable the sharing metadata and enable control across the planning and software development life cycle.  Tools added together are designed to improve database availability – and visibility—and elevate productivity.

Alan R. Earls is a business and technology writer based near Boston.

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