How Will The Data Economy Impact Enterprise Architects?

No self-respecting EA professional would enter into planning discussions with business or tech management execs without a solid grasp of the technologies available to the enterprise, right? But what about the data available to the enterprise? Given the shift towards data-driven decision-making and the clear advantages from advanced analytics capabilities, architecture professionals should be coming to the planning table with not only an understanding of enterprise data, but a working knowledge of the available third-party data that could have significant impact on your approach to customer engagement or your B2B partner strategy.
 
 
Data discussions can't be simply about internal information flow, master data, and business glossaries any more. Enterprise architects, business architects, and information architects working with business execs on tech-enabled strategies need to bring third-party data know-how to their brainstorming and planning discussions. As the data economy is still in its relatively early stages and, more to the point, as organizational responsibilities for sourcing, managing, and governing third-party data are still in their formative states, it behooves architects to take the lead in understanding the data economy in some detail. By doing so, architects can help their organizations find innovative approaches to data and analytics that have direct business impact by improving the customer experience, making your partner ecosystem more effective, or finding new revenue from data-driven products.
 
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Welcome To The Future Of Data Management

 The demand for data has never been greater.  The expectations are even grander.  On the other hand, what the business wants has never been more ambiguous.  

Welcome to the future of data management.  

According to recent Forrester research, most of us are ill prepared.

  • The business is placing the ownership on data professionals for data needs they don't have the full knowledge to enable: security, quality, business intelligence, and data strategy. 
  • Pressure to contain cost causes data professionals to focus on bottom line efficiency goals and de-emphasize top line business growth goals.
  • Investment in data  is still grounded in bespoke systems that lack scale, flexibility, and agility
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