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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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How to Improve Data Quality by Using Feedback Loops

Dataversity

In this blog, we will take a look at: The impact poor Data Quality has on organizations and practical advice for how to overcome this challenge through the use of feedback loops. Poor Data Quality can cost organizations millions each year. It can lead to incorrect decisions, […].

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Why Is Data Quality Still So Hard to Achieve?

Dataversity

In fact, it’s been more than three decades of innovation in this market, resulting in the development of thousands of data tools and a global data preparation tools market size that’s set […] The post Why Is Data Quality Still So Hard to Achieve? appeared first on DATAVERSITY.

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How to Assess Data Quality Readiness for Modern Data Pipelines

Dataversity

The key to being truly data-driven is having access to accurate, complete, and reliable data. In fact, Gartner recently found that organizations believe […] The post How to Assess Data Quality Readiness for Modern Data Pipelines appeared first on DATAVERSITY.

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6 Big Data Mistakes You Must Avoid At All Costs

Smart Data Collective

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

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Data Lakes Are Dead: Evolving Your Company’s Data Architecture

Dataversity

How can your company redesign its data architecture without making the same mistakes all over again? The data we produce and manage is growing in scale and demands careful consideration of the proper data framework for the job. There’s no one-size-fits-all data architecture, and […].

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How to Architect Data Quality on Snowflake

Dataversity

With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical. While existing Data Quality solutions provide the ability to validate Snowflake data, these solutions rely on a rule-based approach that is […].