Big data in EA topic of Siemens conference
by Stephanie Koons, writer/editor for the College of IST
Big Data, which refers to large amounts of structured and unstructured data that require machine-based systems and technologies in order to be fully analyzed, holds enormous potential for organizations. Implementing enterprise –wide systems to harness the power of big data, however, poses challenges for companies. Dr. Brian Cameron, Executive Director of the Center for Enterprise Architecture (EA) at Penn State’s College of Information Sciences and Technology, recently was the keynote speaker at a conference of an international conglomerate, where he discussed how the practice of enterprise architecture—the alignment of enterprise information systems and technology with business strategy and goals—can be employed by companies to develop effective enterprise-wide big data environments.
“Enterprise architecture is the missing bridge needed in many organizations to link strategy and execution,” Cameron said.
Cameron gave the keynote address at the Siemens Global Semantic Technologies for Enterprise Data and System Integration Conference, which was held recently in Princeton, N.J. and attended by about 150 Siemens executives from around the globe. Siemens is a German multinational engineering and electronics company headquartered in Munich, Germany, and specializes in industry, energy, transportation and healthcare.
The Center for EA, which launched in January 2011, seeks to gather intellectual resources across Penn State to address research concerns and questions that span the design, functioning and governance of contemporary, information-driven enterprises. Enterprise architecture, according to Cameron, is the process of translating a business vision and strategy into effective operational planning.
One of the major challenges that companies face in maximizing big data opportunities, Cameron said, is accessing the many silos of data throughout an organization. Enterprise architecture, he added, provides the ability to analyze, design, plan, and implement the enterprise-wide systems needed to effectively utilize massive amounts of data from all silos.
“Effective enterprise-wide big data solutions are difficult to implement without the analysis, design, planning and implementation normally attributed to EA,” he said.