Traditional methods of designing, developing, and implementing data warehouses consume prohibitively large amounts of time and resources. The multi-month, error-prone ETL development effort to set up a data warehouse – typically 60-80% of prep time – often means that the data model is out-of-date before the BI project even starts. Modifying these brittle data warehouses causes more delays, ties up skilled resources and delays project ROI. In short, data warehouses become a bottleneck as much as an enabler of analytics.
To speed time to analytics, the data warehouse creation and management lifecycle must be streamlined wherever possible. BI teams must tackle strategic business questions with as little tactical, administrative work as possible. The processes of extracting data from disparate source systems and wrangling it into the data warehouse are ripe for automation.
Attunity Compose Türkçe Whitepaper dökümanını indirebilmek için lütfen aşağıdaki bilgileri doldurunuz.
The Attunity Compose platform automates the manual, repetitive aspects of data warehouse design, development, testing, deployment, operations, impact analysis, and change management. By simplifying ETL, development and deployment tasks, Attunity Compose empowers BI teams to flexibly deliver timely insights to the business.
With Attunity Compose, IT teams can promptly scope, commit to and rapidly execute on BI projects, freeing up resources and accelerating ROI.
Attunity Compose accelerates data warehouse development and change cycles while ensuring quality and consistency. BI teams gain the time and flexibility they need to focus on reporting and analysis rather than ETL code. Key capabilities include:
- Data model-driven data warehouse and data mart generation
- Real-time source data integration and automated ETL
- Physical data warehouse management
- Lineage and Impact Analysis
- Migration between environments (DTAP)
Attunity Compose supports the major enterprise data warehouses, including Teradata, Oracle/Exadata, IBM Netezza, SQL Server and MySQL