Online Analytical Processing

OLAP Database Solutions

Relational database queries stored into OLAP cubes (matrix) allow for instant access of large database data.

Business Intelligence involves the viewing of OLAP cube database date in Excel Pivot Tables.

OLAP Solutions for Database Queries

OLAP (Short for Online Analytical Processing) is the highly specialized, yet powerful technology behind many BI (Business Intelligence ) and subsequently, Management Information Systems applications. It’s multidimensional analysis of data including data mining, querying, relational databases and reporting, and tremendous speed make it superior in its field.

OLAP digests immense amounts of data using it’s intuitive multi dimensional database and discovery algorithm, which enables users to easily extract complex queries, such as customized report viewing, budgeting, forecasting projections, financial reporting, marketing, sales, management reporting, predictive “what if” scenarios (such as changing fees or opening new locations, staff adjustments), long term projections, analysing trends over a span of years, and any other customized data extraction.

OLAP makes data retrieval real-time and immensely swift for strategic decision making. It is commonly used in applications wherever large storage data at-hand retrieval is necessary and cost control is paramount, including law firms, professional service industries and even agriculture.


Whether the same set of data is called on for sales trends, regional reports, comparative reports, personnel productivity, and multifaceted reports by user, region, expenditures, capital expenses, complex financial data mining – pinpointing a certain financial transaction through a myriad of data, OLAP ideally can do and find it all.

OLAP’s tools enable users to view data in 3 main ways:
OLAP’s tools enable users to view data in 3 main ways:
• Consolidation (roll up) – OLAP’s system accrues all available data and processes it with its algorithm – this allows for example reports with customized and various data set patterns to be viewed simultaneously
• Drill Down – disseminating information into bite size pieces such that the system can recall smaller portions instead of a block of data – this allows for users to pinpoint a transaction or query – especially useful in finding financial transactions, for example
• Slicing and Dicing – the OLAP analysis digitally surgically splices the information then analyzes it by various angles – this allows for data to be profiled, evaluated and shuffled like a 3D deck of cards and the information redistributed in any form required – such as effectiveness of a digital marketing campaign or efficiency and cost effectiveness of a employees in a specified region or sales process, for example.