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Five Factors Driving Data-Intensive Information Architectures

Digital transformation is driving organizations to become much more data intensive. Organizations now process information from an increasing number of internal and external sources. There are many more devices generating information, including IoT sensors. The consumerization of IT and the focus on improving customer, partner and workplace experiences requires organizations to be more responsive. This digitization is leading to a proliferation of different types of databases built to process different types of information. Our research shows nearly two-thirds (63%) of organizations are using three or more different database technologies in their analytics and data processes.

Here are five factors creating requirements for data-intensive applications and some suggestions for information architectures to handle these requirements.

 
 

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About the Author

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David Menninger

SVP and Research Director
Ventana Research

David Menninger is responsible for the overall direction of research on data and analytics technologies at Ventana Research. He covers major areas including artificial learning and machine learning, big data, business intelligence, collaboration, data science and information management along with the additional specific research categories including blockchain, data governance, data lakes, data preparation, embedded analytics, natural language processing (NLP) and IoT.