Dataversity

NOVEMBER 1, 2021

Many in enterprise Data Management know the challenges that rapid business growth can present. Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers. The enterprise […].

Data Governance 130

Data Governance Government Data Management Master Data Management 130

Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

Astera

JANUARY 2, 2024

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

BizAcuity

APRIL 14, 2022

Big Data Ecosystem. Big data paved the way for organizations to get better at what they do. Data management and analytics are a part of a massive, almost unseen ecosystem which lets you leverage data for valuable insights. Data Management. Unscalable data architecture. Slow query performance.

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

Astera

APRIL 3, 2024

As important as it is to know what a data quality framework is, it’s equally important to understand what it isn’t: It’s not a standalone concept—the framework integrates with data governance, security, and integration practices to create a holistic data ecosystem. Why do you need a data quality framework?

Data Quality 52

Data Quality Data Governance Government Monitoring 52

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52