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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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Sure, Trust Your Data… Until It Breaks Everything: How Automated Data Lineage Saves the Day

Octopai

This challenge is especially critical for executives responsible for data strategy and operations. Here’s how automated data lineage can transform these challenges into opportunities, as illustrated by the journey of a health services company we’ll call “HealthCo.”

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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

The data mesh debate This is not to say that there is a consensus that data mesh is a universal solution. Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies.

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Data is Risky Business: The Darker Side of Data Monetization

TDAN

We have seen an impressive amount of hype and hoopla about “data as an asset” over the past few years. And one of the side effects of the COVID-19 pandemic has been an acceleration of data transformation in organisations of all sizes.

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Data is Risky Business: The Next Normal

TDAN

Taking Stock A year ago, organisations of all sizes around the world were catapulted into a cycle of digital and data transformation that saw many industries achieve in a matter of weeks in what would otherwise have taken many years to achieve. Small businesses pivoted to doing business online in a way that they might […].

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Tackling AI’s data challenges with IBM databases on AWS

IBM Big Data Hub

For existing IBM on-premises database customers, transitioning to AWS is seamless, offering risk-free, like-for-like upgrades. Integrate seamlessly with watsonx.data SaaS and other IBM and AWS services like IBM data fabric, Amazon S3, Amazon EMR, AWS Glue and more to scale analytics and AI workloads across the enterprise. Existing

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What companies get wrong about data transformation

CIO Business Intelligence

I think that speaks volumes to the type of commitment that organizations have to make around data in order to actually move the needle.”. So if funding and C-suite attention aren’t enough, what then is the key to ensuring an organization’s data transformation is successful? Anatomy of a data strategy.