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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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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

“We are also working to factor in the COVID impact when making sense of the data and, more importantly, when communicating it.”. Chris and his team are increasing the volume of data being captured and using automation to augment their data strategy : “This is a real jump forward for us.

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The Need for Speed: Faster Data Access as Competitive Edge

Sisense

In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. The world of data is constantly changing and speeding up every day.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

Australian research and advisory firm Adapt identifies an organisation’s ability to execute a data-driven strategy as one of 12 core competencies , identified from 30,000 conversations spanning three years with leading IT and businesses. This is the first post in a series of three on data-driven organisations.