Remove Automation Remove Data Discovery Remove ETL
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What is ETL? Top ETL Tools

Marktechpost

Extract, Transform, and Load are referred to as ETL. ETL is the process of gathering data from numerous sources, standardizing it, and then transferring it to a central database, data lake, data warehouse, or data store for additional analysis. Involved in each step of the end-to-end ETL process are: 1.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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IBM watsonx Platform: Compliance obligations to controls mapping

IBM Journey to AI blog

IBM watsonx™ can be used to automate the identification of regulatory obligations and map legal and regulatory requirements to a risk governance framework. This approach enables centralized access and sharing while minimizing extract, transform and load (ETL) processes and data duplication.

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Build trust in banking with data lineage

IBM Journey to AI blog

This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change? Moreover, banks must stay in compliance with industry regulations like BCBS 239, which focus on improving banks’ risk data aggregation and risk reporting capabilities.

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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. As previously mentioned, a data fabric is one such architecture.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

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What is Data Ingestion? Understanding the Basics

Pickl AI

Enhanced Data Utilisation Effective ingestion unlocks the full potential of data by making it available for advanced analytics, machine learning, and artificial intelligence applications, driving innovation and business growth. Data Ingestion Tools To facilitate the process, various tools and technologies are available.