Smart Data Collective

APRIL 29, 2020

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. Master data management.

Data Management 211

Data Management Data Warehouse Master Data Management Digital Transformation 211

Astera

MAY 14, 2024

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

Government 52

Government Data Governance Master Data Management Documentation 52

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)? Management of all enterprise data, including master data.

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

BizAcuity

APRIL 14, 2022

Data management and analytics are a part of a massive, almost unseen ecosystem which lets you leverage data for valuable insights. According to Gartner, through 2025, 80% of the organizations seeking to scale their digital business will fail because they do not take a modern approach to data and analytics governance.

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

Astera

JANUARY 2, 2024

Free Download Here’s what the data management process generally looks like: Gathering Data: The process begins with the collection of raw data from various sources. Once collected, the data needs a home, so it’s stored in databases, data warehouses , or other storage systems, ensuring it’s easily accessible when needed.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 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