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Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance

Dataversity

The post Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance appeared first on DATAVERSITY. They want to improve their decision making, shifting the process to be more quantitative and less based on gut and experience.

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Data Governance, Data Leadership or Data Architecture: What Matters Most?

Dataversity

Robert Seiner and Anthony Algmin faced off – in a virtual sense – at the DATAVERSITY® Enterprise Data World Conference to determine which is more important: Data Governance, Data Leadership, or Data Architecture. The post Data Governance, Data Leadership or Data Architecture: What Matters Most?

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Use Case Analysis for Business Intelligence Projects

Business Analysis Knowledge Share

This data, if harnessed effectively, can provide valuable insights that drive decision-making and ultimately lead to improved performance and profitability. This is where Business Intelligence (BI) projects come into play, aiming to transform raw data into actionable information.

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

Data Pine

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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The Declarative Approach in a Data Playground

Dataversity

In my first business intelligence endeavors, there were data normalization issues; in my Data Governance period, Data Quality and proactive Metadata Management were the critical points. The post The Declarative Approach in a Data Playground appeared first on DATAVERSITY. But […].

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Data Quality Is In the Eye of the Beholder

The Data Administration Newsletter

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […]. We know the phrase, “Beauty is in the eye of the beholder.”1

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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.

Big Data 280