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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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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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Unlocking the Power of AI with a Real-Time Data Strategy

CIO Business Intelligence

Investments in artificial intelligence are helping businesses to reduce costs, better serve customers, and gain competitive advantage in rapidly evolving markets. Demand for real-time AI is accelerating Software applications enable businesses to fuel their processes and revolutionize the customer experience.

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5 surefire ways to derail a digital transformation (without knowing it)

CIO Business Intelligence

But are product managers developing market- and customer-driven roadmaps and prioritized backlogs? Digital transformations derail when CIOs miss the opportunity to establish and communicate product management responsibilities for creating and evolving market- and customer-driven roadmaps.

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How Data Cleansing Can Make or Break Your Business Analytics

Smart Data Collective

Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. One of the biggest issues pertains to data quality.

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Your Data Won’t Speak Unless You Ask It The Right Data Analysis Questions

datapine

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. They form the bedrock for the rest of this process.

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