What is olap server

Next Continue. Home Testing Expand child menu Expand. SAP Expand child menu Expand. Web Expand child menu Expand. Must Learn Expand child menu Expand. Big Data Expand child menu Expand. Live Project Expand child menu Expand. AI Expand child menu Expand. Toggle Menu Close. Search for: Search. In HOLAP approach the aggregated totals are stored in a multidimensional database while the detailed data is stored in the relational database.

Measure A set of values in a cube that are based on a column in the cube's fact table and that are usually numeric values.

Measures are the central values in the cube that are preprocessed, aggregated, and analyzed. Common examples include sales, profits, revenues, and costs. Member An item in a hierarchy representing one or more occurrences of data. A member can be either unique or nonunique. For example, and represent unique members in the year level of a time dimension, whereas January represents nonunique members in the month level because there can be more than one January in the time dimension if it contains data for more than one year.

Calculated member A member of a dimension whose value is calculated at run time by using an expression. Calculated member values may be derived from other members' values.

For example, a calculated member, Profit, can be determined by subtracting the value of the member, Costs, from the value of the member, Sales.

Dimension A set of one or more organized hierarchies of levels in a cube that a user understands and uses as the base for data analysis. Or, a time dimension might include a hierarchy with levels for year, quarter, month, and day. In a PivotTable report or PivotChart report, each hierarchy becomes a set of fields that you can expand and collapse to reveal lower or higher levels.

Hierarchy A logical tree structure that organizes the members of a dimension such that each member has one parent member and zero or more child members. A child is a member in the next lower level in a hierarchy that is directly related to the current member. A parent is a member in the next higher level in a hierarchy that is directly related to the current member.

The parent value is usually a consolidation of the values of all of its children. Level Within a hierarchy, data can be organized into lower and higher levels of detail, such as Year, Quarter, Month, and Day levels in a Time hierarchy.

Creating cube files for offline use You can create an offline cube file. Use offline cube files to work with OLAP data when you are not connected to your network. A cube enables you to work with larger amounts of data in a PivotTable report or PivotChart report than you could otherwise, and speeds retrieval of the data. Server Actions A server action is an optional but useful feature that an OLAP cube administrator can define on a server that uses a cube member or measure as a parameter into a query to obtain details in the cube, or to start another application, such as a browser.

KPIs A KPI is a special calculated measure that is defined on the server that allows you to track "key performance indicators" including status Does the current value meet a specific number? When these are displayed, the Server can send related icons that are similar to the new Excel icon set to indicate above or below status levels such as a Stop light icon or whether a value is trending up or down such as a directional arrow icon.

Dice selects two or more dimensions from a given cube and provides a new sub-cube. Consider the following diagram that shows the dice operation. The dice operation on the cube based on the following selection criteria involves three dimensions. The pivot operation is also known as rotation. It rotates the data axes in view in order to provide an alternative presentation of data. RDBMS already comes with a lot of features.

A MOLAP system is based on a native logical model that directly supports multidimensional data and operations. Data are stored physically into multidimensional arrays, and positional techniques are used to access them. One of the significant distinctions of MOLAP against a ROLAP is that data are summarized and are stored in an optimized format in a multidimensional cube, instead of in a relational database.

In MOLAP model, data are structured into proprietary formats by client's reporting requirements with the calculations pre-generated on the cubes. MOLAP structure primarily reads the precompiled data. MOLAP structure has limited capabilities to dynamically create aggregations or to evaluate results which have not been pre-calculated and stored. Applications requiring iterative and comprehensive time-series analysis of trends are well suited for MOLAP technology e.

Examples include Arbor Software's Essbase. Some of the problems faced by clients are related to maintaining support to multiple subject areas in an RDBMS. This can be very useful for organizations with performance-sensitive multidimensional analysis requirements and that have built or are in the process of building a data warehouse architecture that contains multiple subject areas.

An example would be the creation of sales data measured by several dimensions e. This structure would be provided to reduce the application overhead of performing calculations and building aggregation during initialization.

These structures can be automatically refreshed at predetermined intervals established by an administrator. Can perform complex calculations: All evaluation have been pre-generated when the cube is created.

Hence, complex calculations are not only possible, but they return quickly. Limited in the amount of information it can handle: Because all calculations are performed when the cube is built, it is not possible to contain a large amount of data in the cube itself. Requires additional investment: Cube technology is generally proprietary and does not already exist in the organization.

Therefore, to adopt MOLAP technology, chances are other investments in human and capital resources are needed.