A Flexible Data Architecture Is a Critical Foundation for Analytics, AI, and Delivering Data as a Service, Says MIT Technology Review Insights
A new report by MIT Technology Review Insights explores how chief data officers and heads of analytics at leading organizations are building data infrastructures, services, and use cases that drive business value. It examines the tensions and trade-offs in different architectures and approaches, and the goals that data executives have for delivering “data as a service” in the years ahead.
The report, “Data on demand: Dynamic architecture for a high-speed age,” is written in association with TIBCO, and is based on in-depth interviews with data and analytics leaders at public- and private-sector organizations including J.P. Morgan Corporate and Investment Bank, Thomson Reuters Labs, Rakuten, the City of London, ABB Group, and the State of North Dakota. The findings are as follows:
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- Companies are using enterprise data strategies to drive business value chains. Data chiefs are developing tailor-made architectures and platforms aligned to their organization’s business model, goals, and key performance indicators.
- Data leaders are analyzing existing and new data sets for hidden value. This may involve breaking down organizational silos and encouraging internal data sharing, or making sense of unstructured data sets and integrating these insights into process flows. There is also increasing interest in exploring how external data sets can be used to inform decisions.
- There are many decisions and trade-offs to be made regarding data architecture. There is no one-size-fits-all and choices must be made, particularly about selecting data sets to integrate and how to provide access. Innovative approaches and technologies for metadata management are emerging.
- Analytics teams must strike a balance between providing access and maintaining control. One of the significant tensions in data governance is providing transparency and access for those who need it, and robust controls that safeguard compliance. Architectures that are too open can, paradoxically, suffer from a lack of transparency over who is accessing what and why.
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“On one hand creating the right architecture is a big technical challenge, on the other it’s the first step in a huge business transformation,” says Claire Beatty, editor of the report. “There are many models that companies can adopt, but ultimately the shared goal is to increase the quality of business decision-making and to accelerate innovation.”
“Today’s data-driven organizations require a new generation of data management capabilities,” said Christophe Barriolade, senior vice president and general manager, TIBCO. “By coupling data virtualization, master data management, and metadata management in an integrated enterprise data fabric, organizations can orchestrate access to multiple and varied data sources and deliver a trusted data services foundation.”
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