Precisely

JANUARY 9, 2025

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

Data Warehouse 119

Data Warehouse Hadoop Data Governance Data Lakes 119

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

JANUARY 13, 2022

Data mesh forgoes technology edicts and instead argues for “decentralized data ownership” and the need to treat “data as a product”. Gartner on Data Fabric. Moreover, data catalogs play a central role in both data fabric and data mesh. We’ll dig into this definition in a bit. Design concept.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

Alation

DECEMBER 21, 2022

MDM is a discipline that helps organize critical information to avoid duplication, inconsistency, and other data quality issues. 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.

Data Quality 52

Data Quality Data Warehouse Data Profiling Data Governance 52

phData

JANUARY 10, 2024

This tool provides functionality in a number of different ways based on its metadata and profiling capabilities. Imagine you wanted to build a dbt project for your existing source data warehouse in your migration to Snowflake. While this may seem like a trivial thing in concept, it’s actually incredibly powerful.

Data Warehouse 52

Data Warehouse Data Profiling Data Pipeline Database 52

Alation

AUGUST 26, 2021

And types of metadata — or data about data — abound. Some high-level metadata categories in a data catalog include: Behavioral : Records who is using data, and how they are using it. Technical: Shows schema or table definitions. Business: Policies on how to handle different kinds of data appropriately.

Data Governance 64

Data Governance ML ML Augmented Analytics 64