An expert in enterprise data architecture, IDERA’s Ron Huizenga joined several other panelists on a DMRadio session called “Method to the Madness: New Roles for the Information Architect” to discuss what’s going on and where things are headed in the information architecture arena. The role of the information architect (IA) is becoming more critical to businesses as they recognize the importance of data. The IA now has to play a different role and map out the information landscape with diverse data sources, including big data.
If you want to leverage and operationalize data proactively, you need to invest in your underlying data architecture and compile the information map for your organization. Data quality is more important now than ever before, and it should be categorized and correlated to validate that it is meaningful to the business. For example, to put together a profile for a customer, you need to assess your internal data against any external information about customers and market trends.
A solid information architecture will also set up your foundation for a data governance program. You have to know what the data is and assign business meaning to it, with the proper terminology. You can define what information is considered sensitive, and run audits against it. You need a data modeling tool to build out schemas and glossaries that describe all of your data and metadata effectively so that good business decisions can be made. With the ER/Studio data modeling suite, you can deliver the proper data with valuable meaning to your business at the right time and in real time.
Adding big data to the equation makes it even more interesting. When you are looking at the information technology within your company, you will probably find a variety of data sources and data stores, including relational databases, big data platforms, data warehouses, ERP solutions, SAS solutions, and more. The ability to visually model and map out all of the data from these sources, and track data lineage between them, can help you understand the information in the organization and build quality into the data process. To effectively assemble and utilize the information, you need a business-driven data architecture design.
Ron Huizenga also presented a summary of Enterprise Architecture frameworks and design considerations in the recent Quack Chat presentation, ER/Studio: The Foundation for your Enterprise Architecture. He also explains how ER/Studio helps you develop your enterprise architecture across the pillars of data, business, technology, and applications.
To effectively develop an enterprise architecture, your technical and business teams need to collaborate on a common data architecture as the underlying foundation to avoid having a mish-mash of conflicting information. This includes identifying what’s important, how it fits together, and how to optimize it, in order to align with business strategy. It will help to document key terms and definitions in a common business glossary to take those disparate data sources and align them to corporate objectives and business strategy.
A solid data architecture is fundamental to defining a higher-order enterprise architecture. That drives enterprise enablement and alignment to strategic goals. Then for the enterprise architecture itself, you have to figure out what the major deliverables are and work from there to establish appropriate business processes, technology and application requirements, and then down to detailed representations for data and metadata.
If you are looking for a tool that can help you with these key data architecture issues, you can try ER/Studio Enterprise Team Edition for free.