Remove Business Intelligence Remove Data Lakes Remove Data Profiling
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Data Integrity for AI: What’s Old is New Again

Precisely

Data marts involved the creation of built-for-purpose analytic repositories meant to directly support more specific business users and reporting needs (e.g., But those end users werent always clear on which data they should use for which reports, as the data definitions were often unclear or conflicting. A data lake!

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

Data Profiling and Data Analytics Now that the data has been examined and some initial cleaning has taken place, it’s time to assess the quality of the characteristics of the dataset. You can even connect directly to 20+ data sources to work with data within minutes.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse. Further processes or workflows can then easily utilize this data to create business intelligence and analytics solutions. This involves looking at the data structure, relationships, and content.

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