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Which Team Should Own Data Quality?

Towards Data Science

This post will focus on the most common team ownership models including: data engineering, data reliability engineering, analytics engineering, data quality analysts, and data governance teams. Why is data quality ownership important? The governance team treats every team output as a data product.

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Who Is Responsible For Data Quality? 5 Different Answers From Real Data Teams

Monte Carlo

This post will focus on the most common team ownership models including: data engineering, data reliability engineering, analytics engineering, data quality analysts, and data governance teams. Table of Contents Why is important to answer who is responsible for data quality?

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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

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2020 Data Impact Award Winner Spotlight: Merck KGaA

Cloudera

This is what really stood out about the finalists of the Data Security and Governance category. These customers have embedded security and governance throughout their entire data and analytics lifecycle by design. It established a data governance framework within its enterprise data lake.

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5 Examples of Bad Data Quality in Business — And How to Avoid Them

Monte Carlo

TABLE OF CONTENTS Unity Technologies’ $110M Ad Targeting Error Unity Technologies, notable for its popular real-time 3-D content platform, experienced a significant data quality incident in Q1 2022. Testing your data early and often helps detect common quality issues before they have the chance to impact downstream data consumers or products.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

The goal is to provide a comprehensive guide that can be a navigational tool for all specialists plotting their course in today’s data-driven world. What is a data lake? A data lake is a centralized repository designed to hold vast volumes of data in its native, raw format — be it structured, semi-structured, or unstructured.