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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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7 enterprise data strategy trends

CIO Business Intelligence

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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Is your data strategy ready for gen AI? LOB leaders may disagree

CIO Business Intelligence

Rapid advancements in artificial intelligence (AI), particularly generative AI are putting more pressure on analytics and IT leaders to get their houses in order when it comes to data strategy and data management. But the enthusiasm must be tempered by the need to put data management and data governance in place.

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6 strategic imperatives for your next data strategy

CIO Business Intelligence

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. For example, you can use C360 to segment and create marketing campaigns that are more likely to resonate with specific groups of customers. faster time to market, and 19.1%

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What is your data strategy for an AI future?

CIO Business Intelligence

While the CEO lost his job, the parent company, Arena Group, lost 20% of its market value. However, access to reliable and trusted data available at the scale needed by enterprises is already a bottleneck that CIOs and other business leaders have to find ways to remedy before it’s too late.

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Practical Skills for The AI Product Manager

O'Reilly on Data

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.