Remove Artificial Intelligence Remove Data Lakes Remove Data Quality
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Data Integrity for AI: What’s Old is New Again

Precisely

Artificial Intelligence (AI) is all the rage, and rightly so. Which of course led to the adoption of data quality software as part of a data warehousing environment with the goal of executing rules to profile cleanse, standardize, reconcile, enrich, and monitor the data entering the DW to ensure it was fit for purpose.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

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A Bridge Between Data Lakes and Data Warehouses

Dataversity

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

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Data Swamp, Data Lake, Data Lakehouse: What to Know

Alation

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data. and various countries in Europe.

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Data Engineering for IoT Applications: Unleashing the Power of the Internet of Things

Data Science Connect

This data is then integrated into centralized databases for further processing and analysis. Data Cleaning and Preprocessing IoT data can be noisy, incomplete, and inconsistent. Data engineers employ data cleaning and preprocessing techniques to ensure data quality, making it ready for analysis and decision-making.

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What is a data fabric?

Tableau

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

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