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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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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architect vs. data engineer The data architect and data engineer roles are closely related.

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CIO Ryan Snyder on the benefits of interpreting data as a layer cake

CIO Business Intelligence

Martha Heller: What are the business drivers behind the data architecture ecosystem you’re building at Thermo Fisher Scientific? Ryan Snyder: For a long time, companies would just hire data scientists and point them at their data and expect amazing insights. That strategy is doomed to fail.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Bridge the data literacy skills gap with data storytelling

IBM Big Data Hub

Being a data-driven organization goes well beyond building a modern data architecture. For CDOs and other leaders within different lines of business, this means fostering a culture that prioritizes data literacy : the ability to read, understand, create and communicate data.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

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Achieving Trusted AI in Manufacturing

Cloudera

Here are some of the key use cases: Predictive maintenance: With time series data (sensor data) coming from the equipment, historical maintenance logs, and other contextual data, you can predict how the equipment will behave and when the equipment or a component will fail.