Online Analytical Processing (OLAP): An Overview

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Online Analytical Processing or OLAP is a computer processing or an approach that answer multidimensional queries from users in a fast manner.  The term OLAP appeared only during 1993 with the help of by Edgar Codd. He is also known as the “Father of the Relational Database”. The three systems of OLAP are multi-dimensional OLAP (MOLAP), Hybrid OLAP and relational OLAP (ROLAP). The three systems allow rapid access to data from analytical processing. They also have their own benefits and uses.

MOLAP is for summary database, ROLAP uses relational databases and HOLAP utilizes relational tables to produce multidimensional ones. OLAP are intelligence systems organized and stored in data warehouses. Data warehouses have been a good help among companies these recent years. These data warehouses are used to analyze and explain complicated OLAP systems and processes that are critical for an organization to stay competitive in the market business.

OLAP provides users an access to different data from different or multidimensional viewpoints. For example, a user wants to know the different prices and amenities of hotels in a certain city. OLAP will provide a spreadsheet of comparison and analysis among hotels in that particular city. OLAP data representations are known as “cubes” which are stored in a multidimensional database. OLAP software, tools, algorithms and applications enable users to analyze data stored in the database in multiple perspectives.

Online analytical processing is a vital tool in any business because it can be very helpful in analyzing the data especially complex ones and improving decision-making in the company.  The use of OLAP is an advantage to the company’s reporting, managing, planning, and budgeting especially when it comes to making a new project. Some of these advantages include easy access to data, accurateness of data, and multidimensional analysis of concepts. OLAP is an important tool in bringing information to decision-making. OLAP is a technology which has a core database that presents different views of the relations of the company’s products, competitors and management items.

Data warehouses use solutions and tools for OLAP to be organized well. These OLAP solutions and tools are multidimensional view of the data (data organized into tables), interactive analysis of the data (uses drill up, drill down and slice data), analytical modeling (tool to calculate ratios and variances), functional model (includes forecasting and trend analysis), and graphical analysis (tool that uses 2D or 3D charts and graphs).

OLAP systems are created to operate and handle queries which require large quantities of data. OLAP designed from operational data is what we call multidimensional cubes. And “measure” is the basic unit used for a multidimensional cube. These multidimensional cubes, when applied, provide a better performance for OLAP compared to ordinary spreadsheets and tables. One of the many reasons why businesses and companies use OLAP is the speed which means OLAP systems offer fast access to large quantities of data.

Since 1996, InetSoft has offered software platform for dashboards, visual analysis, and reporting to be used in conjunction with good OLAP server solution or any combination of open standards data sources.