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The Race For Data Quality in a Medallion Architecture

DataKitchen

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?

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Your Data Won’t Speak Unless You Ask It The Right Data Analysis Questions

datapine

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

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Top 10 Metadata Management Influencers, Sites, and Blogs You Must Follow in 2021

Octopai

He is the President of Knowledge Integrity, Inc and an expert in master data management, data quality, and business intelligence. He is also an author of many books that center around the best practices in business intelligence. IRM UK Connects. It is published by Robert S. Seiner and produced by Dataversity.

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A Big Data Imperative: Driving Big Action

Occam's Razor

All it takes is a little business analysis. Here's my post: Five Steps to Finding a Purpose for your Analysis. When you have access to all this data, the answers you find will be surprising, the insights you deliver will be brilliant, and your impact on the business will be huge. Have something.

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The Book Look: Navigating the Labyrinth – Exec Guide to Data Management

TDAN

The Data Management Body of Knowledge (DMBOK2) is the most comprehensive and objective book on data management. Comparable to what the PMBOK does for project management and the BABOK for business analysis, DMBOK2 provides a detailed framework for organizations to manage their data and mature their information infrastructure.

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Human-centered design and data-driven insights elevate precision in government IT modernization

IBM Big Data Hub

Using data, user research and human-centered design to effectively address these considerations can help you develop a clear modernization strategy that objectively drives your priorities, backlogs and roadmaps. and quality (how does this impact service delivery, business process and data quality?).

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Knowledge Graphs: Redefining Data Management for the Modern Enterprise

Ontotext

They can track data as it flows through the enterprise, monitor its quality, discover errors, and trace them to the source, reducing bad data quality and data duplication. Knowledge graphs provide high-quality data based on enriched and linked metadata.