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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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Common Business Intelligence Challenges Facing Entrepreneurs

datapine

Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors. The power of data analytics and business intelligence is universal. Entrepreneurs And Business Intelligence Challenges. Let’s get started!

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Oracle makes its pitch for the enterprise cloud. Should CIOs listen?

CIO Business Intelligence

Oracle Cloud Infrastructure is now capable of hosting a full range of traditional and modern IT workloads, and for many enterprise customers, Oracle is a proven vendor,” says David Wright, vice president of research for cloud infrastructure strategies at research firm Gartner. The inherent risk is trust.

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CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

When it comes to AI, Nafde sees risks in the vendors selected, the business-worthiness of the use case, and the cost of the initiative. The CIO has strategies in place to address all three. For a typical project that will likely involve a Snowflake data lake hosted currently on Azure, Menon stresses that quality of data is critical. “AI

Risk 133
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Watch Out for Business Intelligence "Gotchas"

Howard Dresner

I kicked off a recent discussion with this question to the group: “What are the top five worst practices in business intelligence?” I certainly don’t want to minimize the great successes organizations are having with business intelligence. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday.

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Dresner’s Point: Ready for the “2014ization” of Business Intelligence?

Howard Dresner

Instead, let’s kick start the year with some definite plans and aspirations of companies in the business intelligence sphere. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. Definitely, they responded.

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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

When it comes to implementing and managing a successful BI strategy we have always proclaimed: start small, use the right BI tools , and involve your team. When encouraging these BI best practices what we are really doing is advocating for agile business intelligence and analytics. Without further ado, let’s begin.