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Eliminate The Overhead In Your Data Integration With The Open Source dlt Library

Data Engineering Podcast

Summary Cloud data warehouses and the introduction of the ELT paradigm has led to the creation of multiple options for flexible data integration, with a roughly equal distribution of commercial and open source options. The challenge is that most of those options are complex to operate and exist in their own silo.

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Data Integrity Trends for 2023

Precisely

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. Data integrity trends for 2023 promise to be an important year for all aspects of data management. Read The Corinium report to learn more.

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Best of 2023: Top 5 Data Integrity Blog Posts

Precisely

Data integrity empowers your businesses to make fast, confident decisions based on trusted data that has maximum accuracy, consistency, and context. As 2023 comes to an end we’re counting down the Top 5 Data Integrity blog posts of the year. #5. Read more > #2.

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Point to Point Data Integration vs Cloud Data Integration: 4 Critical Differences

Hevo

You need data integration for simplified data analytics. Given how siloed data sources have gotten with the evolution of the modern data stack, it’s become even more important to bring data from multiple disparate sources to a central repository. Point to point data […]

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Top 4 Data Integration Tools for Modern Enterprises

KDnuggets

Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises.

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Exploring Innovations in Data Integrity

Precisely

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

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Data Integrity Testing: 7 Examples From Simple to Advanced

Monte Carlo

Well, the same goes for your data. Just because it looked good yesterday doesn’t mean it’ll hold up tomorrow – and that’s why we’re talking about data integrity testing today. Data integrity testing is the process of ensuring data is fit for the task at hand and available to only those who should have access.