Smart Data Collective

APRIL 29, 2020

Data management approaches are varied and may be categorised in the following: Cloud data management. The storage and processing of data through a cloud-based system of applications. Master data management. The tool assigns the role of ‘data stewards’ in an organisation to manage master data.

Data Management 220

Data Management Data Warehouse Master Data Management Digital Transformation 220

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)? Data breaches and regulatory compliance are also growing concerns.

Data Management 52

Data Management Master Data Management Government Data Warehouse 52

Astera

MAY 14, 2024

Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. Examples include actions (such as data cleaning steps), tools used, tests performed, and lineage (data source).

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

JUNE 1, 2023

NoSQL databases come in a variety of types based on their data model. The main types are: Key-value stores: Data is stored in an unstructured format with a unique key to retrieve values. Document databases: Data is stored in document format, such as JSON. Examples are Redis and DynamoDB.

Documentation 52

Documentation E-Commerce Big Data Master Data Management 52

Astera

JUNE 1, 2023

NoSQL databases come in a variety of types based on their data model. The main types are: Key-value stores: Data is stored in an unstructured format with a unique key to retrieve values. Document databases: Data is stored in document format, such as JSON. Examples are Redis and DynamoDB.

Documentation 52

Documentation E-Commerce Big Data Master Data Management 52

Astera

JULY 13, 2023

Data warehouses are designed to support complex queries and provide a historical data perspective, making them ideal for consolidated data analysis. They are used when organizations need a consolidated and structured view of data for business intelligence, reporting, and advanced analytics.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

Astera

JANUARY 2, 2024

Businesses, both large and small, find themselves navigating a sea of information, often using unhealthy data for business intelligence (BI) and analytics. 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.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52