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 209

Data Management Data Warehouse Master Data Management Digital Transformation 209

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 Government Data Warehouse 52

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

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

JULY 13, 2023

One of the key benefits of a data lake is that it can also store unstructured data, such as social media posts, emails, and documents. This makes it a valuable resource for organizations that need to analyze a wide range of data types. Learn more here or get in touch to see how Astera can help.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

JANUARY 2, 2024

Execution and handling of data operations. Objective Ensure data quality, security, and compliance. Efficient and effective handling of data. Activities Policy creation, enforcement, and monitoring. Data collection, storage, processing, and usage. Addresses immediate data handling requirements.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Data Pine

NOVEMBER 27, 2019

It is not only important to gather as much information possible, but the quality and the context in which data is being used and interpreted serves as the main focus for the future of business intelligence. Accordingly, the rise of master data management is becoming a key priority in the business intelligence strategy of a company.

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144