Astera

NOVEMBER 30, 2023

Building upon the strengths of its predecessor, Data Vault 2.0 elevates data warehouse automation by introducing enhanced scalability, agility, and adaptability. It’s designed to efficiently handle and process vast volumes of diverse data, providing a unified and organized view of information. Data Vault 2.0

Data Warehouse 52

Data Warehouse Healthcare Big Data Data Governance 52

Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Government: Using regional and administrative level demographic data to guide decision-making.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Business Analysis Knowledge Share

OCTOBER 27, 2023

Enhanced Data Governance : Use Case Analysis promotes data governance by highlighting the importance of data quality , accuracy, and security in the context of specific use cases. This may involve data from internal systems, external sources, or third-party data providers.

Business Intelligence 52

Business Intelligence Business Intelligence Supply Chain Data Governance 52

Astera

MARCH 30, 2023

It is an integral aspect of data management within an organization as it enables the stakeholders to access and utilize relevant data sets for analysis, decision making, and other purposes. It involve multiple forms, depending on the requirements and objectives of stakeholders.

Data Quality 52

Data Quality Data Warehouse Data Security Finance 52

Astera

NOVEMBER 28, 2023

For instance, they can extract data from various sources like online sales, in-store sales, and customer feedback. They can then transform that data into a unified format, and load it into a data warehouse. Facilitating Real-Time Analytics: Modern data pipelines allow businesses to analyze data as it is generated.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Astera

JUNE 13, 2023

Evolution of Data Pipelines: From CPU Automation to Real-Time Flow Data pipelines have evolved over the past four decades, originating from the automation of CPU instructions to the seamless flow of real-time data. Techniques like data profiling, data validation, and metadata management are utilized.

E-Commerce 52

E-Commerce Data Quality Real-time Data Data Warehouse 52