• Comprehensive data warehouse implementation from
architecture planning, through data modeling, to ETL
• Reporting - from static reports to OLAP cubes.
• Data warehouse management.
Data Warehouse – the foundation of successful Business Intelligence
How can you change your vast mass of raw data into useful information?
Although data warehouses might look old-fashioned, and not-so-fancy today, they still exist and are in use in the background.
The data warehouse's basic requirements have not changed over time. The primary purpose of a data warehouse is to gather, integrate, consolidate a company’s data and to record changes to this data over time. Data assets can originate from various sources: CRM, ERP, engineering systems, transactional systems or even from social media. Architecting a data warehouse is an art of optimizing to fulfilling the business needs by practical use of hardware, software and expert resources and also taking future developments into consideration. While loading the data warehouse, some important data integration, matching and quality improvement operations are done to prepare data for compliant reporting.
By consolidating data, the concepts of different business lines can be transformed into a common business language, allowing users of these different areas to have the same understanding of these concepts. The recording of changes over time is also important, as experience from the past can lead to useful conclusions for the future.
We and our extended team have more than a decade of experience developing data warehouses based on various technologies, including cloud infrastructure. When considering the business needs and the available data sources, we strive for the most cost-effective data warehouse solution for our customers.
Whether it is on the ground, or in the cloud, the data warehouse remains a stable background for your business intelligence purposes, including analytics, dashboards, and reports.