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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Uplevel your data architecture with real- time streaming using Amazon Data Firehose and Snowflake

AWS Big Data

Partner Solutions Architect at AWS and has over 20 years of experience working with database and analytics products from enterprise database vendors and cloud providers. He has helped technology companies design and implement data analytics solutions and products.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

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How data, AI and automation can transform the enterprise

IBM Big Data Hub

Their role has expanded from providing business intelligence to management, to ensuring high-quality data is accessible and useful across the enterprise. In other words, they must ensure that data strategy aligns to business strategy. Building the foundation: data architecture. But the dividends are unmistakable.

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The New Normal for FP&A: Data Analytics

Jedox

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new. Inability to get data quickly.

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Insights from Gartner Data & Analytics Summit Orlando 2023

Alation

Actually, with Solomon-like wisdom, Zaidi and Thanaraj suggest a scenario where data fabric and data mesh work together — a Reese’s Peanut Butter Cup of data architecture, representing a “meshy fabric” scenario I presented last year. Can your stack accommodate the next big thing?