Astera

NOVEMBER 1, 2023

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. While both are meant for storing and retrieving data, they serve different purposes and have distinct characteristics.

Data Warehouse 40

Data Warehouse Real-time Data E-Commerce Data Governance 40

The BAWorld

SEPTEMBER 18, 2024

There exist various forms of data integration, each presenting its distinct advantages and disadvantages. The optimal approach for your organization hinges on factors such as data requirements, technological infrastructure, performance criteria, and budget constraints. Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Actian

OCTOBER 21, 2019

Azure is growing significantly as a platform in the enterprise space and becoming the de-facto choice for retail analytics. This is particularly appealing to those customers who have large amounts of data which is growing quickly but may not need compute to scale at the same pace.

Vision 40

Vision Data Warehouse Retail Data Discovery 40

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

The BAWorld

NOVEMBER 22, 2021

Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Datamart is a subset of a data warehouse focused on a particular line of business, department, or subject area.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

SEPTEMBER 20, 2023

Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and data warehouses for storage and initial processing. Use cases include creating data warehouses, data marts, and consolidated data views for analytics and reporting.

Data Warehouse 52

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

Astera

SEPTEMBER 20, 2023

Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and data warehouses for storage and initial processing. Use cases include creating data warehouses, data marts, and consolidated data views for analytics and reporting.

Data Warehouse 52

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