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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

IoT is basically an exchange of data or information in a connected or interconnected environment. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity.

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Generative AI is pushing unstructured data to center stage

CIO Business Intelligence

Applications such as financial forecasting and customer relationship management brought tremendous benefits to early adopters, even though capabilities were constrained by the structured nature of the data they processed. have encouraged the creation of unstructured data. Artificial Intelligence

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

Webster Bank is following a similar strategy. We’ve established an AI working group with representatives across technology, architecture, data, security, legal, risk, and audit consisting of both technical practitioners and business users to develop AI-use best practices and a governance framework,” says Nafde. Diasio agrees.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS. You’re now ready to query the tables using Athena.

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11 dark secrets of data management

CIO Business Intelligence

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.