Review of Short Phrases and Links|
This Review contains major "Olap"- related terms, short phrases and links grouped together in the form of Encyclopedia article.
- OLAP is a technology that can be distributed to many users using a variety of platforms.
- OLAP is a platform upon which decisions are made.
- OLAP is a specific way of financial and statistical data representation for executives, specialists and analysts.
- OLAP is part of the broader category business intelligence, which also encompasses relational reporting and data mining.
- OLAP is part of the broader category business intelligence, which also includes Extract transform load (ETL), relational reporting and data mining.
- OLAP Services supports a full MOLAP implementation, full ROLAP implementation, or a HOLAP solution.
- OLAP Services does not store empty values, and as a result, even sparsely populated cubes will not balloon in size.
- The result is that OLAP Services derives nonaggregated data from a few existing aggregate values rather than having to scan the entire data warehouse.
- An OLAP database does not need to be as large as a data warehouse, since not all transactional data is needed for trend analysis.
- Furthermore, OLAP Services is optimized for development of data warehouses where star or snowflake schemas have been designed.
- Normally, OLAP databases extract information from several OLTP databases called data warehouses.
- Combining data from multiple fact tables is a difficult problem in the pure relational world, but can be made easy and intuitive in certain OLAP servers.
- It has been claimed that for complex queries OLAP cubes can produce an answer in around 0.1% of the time for the same query on OLTP relational data.
- Distinguish between data mining and OLAP. Explain the relation between data warehousing and data mining.
- A numeric value stored in a fact table and in an OLAP cube.
- The findings of The OLAP Survey 6 are a valuable guide to the product capabilities and after-sale support you can expect from the top BI vendors.
- While OLAP systems have the ability to answer "who" and "what" questions, it's their ability to answer "what if" that sets them apart from other BI tools.
- The authors did a really good job showing how data mining and OLAP can work together to create a BI (Business Intelligence) system.
- We found one for ETL, Jetstream, one OLAP engine, Mondrian, and jPivot, which gave a front end to Mondrian.
- This paper explains the application of business intelligence tools like dataware housing, OLAP, and data mining in insurance.
- OLAP organizes facts into dimensions which are ways that the facts can be broken down.
- Logi OLAP Reporting lets users move dimensions, select different calculations, create interactive charts and graphs and easily drill down into cube data.
- Filtering of hierarchy members with or without applying these filters to the OLAP calculations.
- The key difference between OLAP dimensions and simple relational dimensions is the central role played by hierarchies in OLAP implementations.
- Dimensional model is the underlying data model used by many of the commercial OLAP products available today in the market.
- Few OLAP products, however, have taken advantage of this trend.
- Many of these vendors already are delivering beta products based on the specification to OLAP Services users.
- The obvious benefit is that the OLAP database administrator is better able to translate skills from SQL Server and other Microsoft products.
- In traditional OLAP systems, data that has not been preaggregated is not available for reporting and analysis purposes unless calculated at run time.
- The Analysis Services task processes OLAP cubes that are based on the data.
- The term used in Microsoft's Analysis Services (OLAP Services) for a cube that is created from portions of one or more base cubes.
- This hindered large-scale deployment to many clients, and the use of OLAP data from other vendors.
- Explain Codd’s guidelines for an OLAP system.
- We agree with Dr Codd, but also note that many OLAP applications are still read-only.
- Warehouse management operates to manage the ETL and data quality stage, the Relational OLAP databases and Data Warehouse and the analytical applications.
- The OLAP + CHART ModelKit components package is intended for the creation of analytical applications for decision support systems.
- OLAP common analytical operations Consolidation - involves the aggregation of data i.e.
- These precomputed values, or aggregations, are the basis of the OLAP performance gains.
- These logs can then be used to fine-tune the set of aggregations that OLAP Services maintains.
- The number of aggregations in an OLAP model is a function of the number of dimensions, the number of levels in the hierarchies, and the parent-child ratios.
- Around about V8.5, Holos Server implemented a hierarchical lock manager, allowing nesting of fine and coarse-grain OLAP locks, and full transaction control.
- Datamation maintains a comprehensive web site with information on OLAP and data warehouses.
- PivotTable Service is the facility that connects OLAP client applications to the OLAP Services server.
- Built on the OLE DB for OLAP interfaces, these new capabilities will support live access to OLAP Services servers, disconnected usage, and Web-based access.
- All access to data managed by OLAP Services, by custom programs or client tools, is through the OLE DB for OLAP interface provided by PivotTable Service.
- An OLAP cube is a mechanism to define (and optionally store) aggregations.
- Included in OLAP Services is a full tutorial on OLAP concepts and a step-by-step guide to building an OLAP cube.
- Also called a data mart or OLAP cube.
- The ability to create virtual cubes means that many unnecessary values can be eliminated from the OLAP data storage altogether.
- An ability to edit OLAP data directly in the grid.
- Multidimensional Expressions is a Microsoft -owned query language for OLAP databases.
- As described earlier, OLAP data explosion is the result of multidimensional preaggregation.
- To facilitate this kind of analysis, OLAP data is stored in a multidimensional database.
- Used to link OLAP clients and servers using a multidimensional language, MDX.
- Multidimensional OLAP ("MOLAP") utilizes a proprietary multidimensional database ("MDDB") to provide OLAP analyses.
- Executives and business analysts can view OLAP data by various dimensions, measures, and filters.
- HOLAP can use varying combinations of ROLAP and OLAP technology.
- In its simplest definition, OLAP is a queriable repository against which Microsoft and third-party technologies provide the ability to ask questions.
- An overview of data warehousing and OLAP technology.
- The most common example of HOLAP architecture is OLAP services in Microsoft SQL Server 7.0.
- Missing or invalid data values create sparsity in the OLAP data model.
- Within each dimension of an OLAP data model, data can be organized into a hierarchy that represents levels of detail on the data.
- Star and snowflake schemas are relational approximations of the OLAP data model and can be an excellent starting point for building OLAP cube definitions.
- OLAP ModelKit is designed for multidimensional data analysis.
- OLAP services provide for fast analysis of multi-dimensional information.
- It usually includes one or more data marts or OLAP systems for end-user data analysis.
- Pentaho has also updated the Pentaho Cube Designer to streamline the process of creating OLAP schemas, and to enhance support for "snowflake" schemas.
- OLAP Services can easily accommodate other source schemas should they be encountered.
- SWREG reporter uses SWREG's CSV sales data reports, imports them to a relational database and then processes as a multidimensional (OLAP) cube.
- Dimensionalization - Organizing the data into the multidimensional (OLAP) structure of a star schema.
- MOLAP(Multidimensional OLAP), provides the analysis of data stored in a multi-dimensional data cube.
- The process-driven approach helps Finance & IT Managers analyze ERP, OLAP & relational data systems & Web services simultaneously.
- Speed and response time are important attributes of OLAP services that allow users to browse and analyze data on-line in an efficient manner.
- Open Source OLAP Server for analysis, reporting, budgeting, forecasting, and planning.
- Contact: Gert Jan de Nooij OLAP marketing, sales, marketing research, and sales forecasting consultants with Oracle Express products and Essbase products.
- Analytical applications carry out OLAP analysis using OLAP tools.
- This is accomplished by connecting the data to fast and easy-to-use tools known as Online Analytical Processing (OLAP) tools.
- The SAP business information warehouse enables OLAP for processing of information from large amounts of operative and historical data.
- Data warehouses consolidate data into a central repository and give you the OLAP tools necessary to retrieve data pertinent to the solution.
- First and foremost, OLAP presents data to end users through a natural, intuitive data model.
- Data sparsity is a challenge for OLAP vendors that has been met with varying degrees of success.
- A fundamental challenge in OLAP implementation is mapping the initial database schema to the multidimensional model.
- He could also be interpreted as saying that data changes should not be allowed in what are normally regarded as calculated cells within the OLAP database.
- In fact, in the interests of storing sparse data more compactly, a few OLAP tools such as TM1 do break this rule, without great loss of function.
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