Data processing (ETL), and data warehouse construction
Data processing is a crucial phase of business intelligence data storage.
Business data can come from a variety of sources, can be structured in a variety of ways, according to a variety of standards. Before storage, data needs to be processed, checked for structural integrity, and unified, so that is it stored in the most efficient and convenient manner.
Timing, volume, and structure of data varies greatly from organization to organization. The process of adding or updating data is very much a company-specific operation. Our ETL tools are flexible enough to process any standard data storage format, and the transformation supports data output in a wide variety of standards, resulting in data, that is optimized for a specific company and its business requirements.
A comprehensive reporting system is a tool, that extracts valuable information out of the stored company data. The reporting system can be customized, to serve users on different levels. Top level executives require consolidated business indicators reports, while lower level personnel requires reports, that include more detail about their specific business operations. A good reporting system ensures, that the data is correctly interpreted and comprehensively presented, providing the user with as much information as possible in a compact and flexible output document.
The reporting output can use the Microsoft Reporting platform, or our in-house reporting platform, providing our clients with a choice. The Abraxas reporting platform is being used by a number of banks, who have learned to appreciate the flexibility of our configurable output formats, which is useful for data exports. The Abraxas reporting platform also confirms to a list of requirements, enforced by most national banks.
Introducing OLAP (Online Analytical Processing), OLAP cube construction
OLAP is a significant part of Business Intelligence Services, which provides real-time analysis of stored data. Abraxas OLAP tools include a flexible configuration of filtering, trimming, and user-defined reports. An OLAP system can improve sales analysis, marketing impact analysis, financial trends analysis or other areas, that might be useful for a company.
To create a good real-time analysis report, a set of quick and efficient data queries is required. Due to sheer volume of data, that is usually stored in traditional relational databases, queries can be too slow for real-time analysis. To circumvent that issue, the data is transformed into a specific data structure, called the OLAP cube, which is optimized for quick and efficient data queries, and provides the foundation for real-time analysis of accumulated company data.
Data mining helps users identify hidden characteristics of their specific businesses, and trends in their fields. Typically a data mining operation will reveal correlation between a customer’s characteristics (e.g. age, income, education) and the products, they are most likely interested in buying. Data mining reveals characteristics, that are impossible to discover through standard data analysis, and which are essential for marketing and planning.