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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. What does a modern data architecture do for your business?

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How to Build ETL Data Pipeline in ML

The MLOps Blog

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

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

ODSC - Open Data Science

Great Expectations provides support for different data backends such as flat file formats, SQL databases, Pandas dataframes and Sparks, and comes with built-in notification and data documentation functionality. You can even connect directly to 20+ data sources to work with data within minutes.

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Data integrity vs. data quality: Is there a difference?

IBM Journey to AI blog

The more complete, accurate and consistent a dataset is, the more informed business intelligence and business processes become. This is done to uncover errors, inaccuracies, gaps, inconsistent data, duplications, and accessibility barriers.