What are the applications of OLAP?

OLAP stands for On-Line Analytical Processing. OLAP is an element of software technology that authorizes analysts, managers, and executives to gain insight into data through fast, consistent, interactive access in a wide variety of possible views of information that has been changed from raw information to reflect the actual dimensionality of the enterprise as learned by the client.

OLAP allows the users to generate online descriptive or comparative summaries of data and other analytics queries. It designates an element of software and technologies that enable the collection, storage manipulation, and reproduction of multidimensional data with the aim of analysis.

It allows the decision-makers to profit insight into data through quick consistent and interactive access to a broad variety of possible views of data that has been changed from raw data to the real dimensionality of the attributes.

OLAP servers present business users with multidimensional data from data warehouses or data marts, without concerns regarding how or where the data are saved. The physical structure and execution of OLAP servers should consider data storage issues.

There are various applications of OLAP which are as follows −

Analytical Reporting − Analytical applications support many facets of a business and offer high returns on investment. There are various types of analytical applications which are as follows −

  • Accounting, forecasting, budgeting, cost, and profitability analysis and consolidation.

  • Human resources, skill consolidation, labor scheduling, and optimization.

  • Distribution, scheduling, and optimization.

  • Marketing, churn, and market-based analysis.

  • Retailing, site location, and demographic analysis.

  • Manufacturing, demand planning, and forecasting.

  • Health care, outcome analysis.

  • Financial services, risk assessment, and management.

Predictive analysis − Planning applications allow organizations to predict outcomes. The new data is generated using predictive analytics tools such as models, forecasts, aggregation, allocation, budgeting, and financial analysis, and demand planning systems.

Budgeting and financial analysis systems analyze past performance, build revenue and spending plans, manage towards profit goals, and model the effects of change on the financial plan. Management can determine spending and the effects of change on the financial plan.

Management can determine spending and investment levels that are appropriate for the anticipated events and profit levels. Financial analysts can produce alternative budgets and investment plans contingent on elements including fluctuations in currency values.

The demand planning system allows predicting market demand based on factors such as sales history, promotional plans, pricing models, etc. They can model different scenarios that forecast product demand and then determine appropriate manufacturing goals.