IBM Journey to AI blog

JANUARY 5, 2023

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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Alation

SEPTEMBER 7, 2021

TrustCheck can be integrated with popular business intelligence BI tools, like Tableau, which supply quality information as you use these tools. In addition, Alation provides a quick preview and sample of the data to help data scientists and analysts with greater data quality insights.

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Alation

MAY 24, 2022

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

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Data Quality Data Governance ETL Data Observability 98

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly.

Data Quality 52

Data Quality Data Warehouse Data Profiling Data Governance 52

DagsHub

AUGUST 23, 2024

A data quality standard might specify that when storing client information, we must always include email addresses and phone numbers as part of the contact details. If any of these is missing, the client data is considered incomplete. Data Profiling Data profiling involves analyzing and summarizing data (e.g.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Alation

AUGUST 26, 2021

For this reason, data intelligence software has increasingly leveraged artificial intelligence and machine learning (AI and ML) to automate curation activities, which deliver trustworthy data to those who need it. How Do Data Intelligence Tools Support Data Culture? BI and AI for Data Intelligence.

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The MLOps Blog

MAY 17, 2023

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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Dataconomy

MARCH 26, 2025

These stages ensure that data flows smoothly from its source to its final destination, typically a data warehouse or a business intelligence tool. By facilitating a systematic approach to data management, ETL pipelines enhance the ability of organizations to analyze and leverage their data effectively.

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