Data design tools are naturally associated with front-end design efforts, but they can also enable better data integration, reporting and governance. Leading tools are more than a scratchpad for greenfield designs, experts say. The tools can also inspect an organization's data assets and create a model of the existing data landscape.
Such data discovery traits are important in tool sets such as Dell Quest Toad, Embarcadero ER/Studio, IBM InfoSphere Data Architect, Oracle Endeca Information Discovery and others. One long-time player, CA Technologies, recently updated its ERwin data modeling suite to drive data modeling further into data management.
The recent ERwin release includes improved data integration capabilities and models that spur better data decision-making across groups of enterprise stakeholders. A strong, central metadata repository helps achieve these capabilities, according to an industry analyst.
"The newer, more sophisticated modeling tools have a way of looking at the organization's data landscape," according to Shawn Rogers, vice president of research for business intelligence, data warehousing and analytics at consultancy Enterprise Management Associates Inc. in Boulder, Colo.
CA's ERwin is notable, he said, in that it provides "model-driven metadata exchange and collaboration. Many [modeling] tools are not as integrated into data management."
Using a design tool like CA's ERwin as the center of a data management initiative can help build a single view of a company's overall information architecture -- across a variety of data sources shared with a variety of departments, geographies and roles, according to Donna Burbank, vice president of product marketing for the data management business at CA.
Modeling a Wild West of data
Efforts to discover, catalog and collaborate around corporate data are not made easier, analyst Rogers noted, as wildly diverse big-data types come along. With its latest ERwin version, CA adds support for modeling Hadoop and Hive data -- a first step in tackling new, trending data types.
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While it is still early, data design tools and data modeling tools that support new Hadoop and NoSQL architectures -- as well as more varied data types -- could bring a bit more rationality to budding big data efforts in which models and schema may not be done upfront.
"Though most of the modern [databases] labeled "NoSQL" are schema-less, it is possible to have tools which intuit patterns in the data and extract what might be implicit models," according to Al Hilwa, program director for software development research at IDC.
"The explosion in big data creates opportunities for these tools, and we are seeing the players begin to position for these changes," he said.
Taking it to the Banco
ERwin's reporting capabilities are a plus, allowing various stakeholders to work together on "data-intensive" initiatives, according to ERwin user Gonzalo Vallejo, chief data architect at Chile-based Banco Estado.
At Banco Estado, there is need right now "to employ graphical and text reports that serve both business and technical users," he said.
"The ERwin metadata repository offers the right tool to store and explore data definitions and their relationships," he said.
Vallejo said he sees modeling tools like ERwin leading to better data governance. "This is not a miracle, it is the result of the medium- to long-term discipline," he said.
Support for newer software architectures like Hadoop and HBase are of less immediate importance to Vallejo, who said it would be "probably some years forward" before his group would advance to this step.