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.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

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.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

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.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

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

The MLOps Blog

MAY 17, 2023

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. Basic ETL pipelines are batch-oriented, where data is moved in chunks on a specified schedule.

ETL 59

ETL Data Pipeline ML ML 59