roll-up in data warehouse

Roll-up is performed by climbing up a concept hierarchy for the dimension location. ... On rolling up, the data is aggregated by ascending the location hierarchy from the level of city to the level of country. The data is grouped into cities rather than countries.

1. What is roll-up in OLAP?
2. What is rollup and drill down?
3. What is slice and dice in data warehouse?
4. What is OLAP in database?
5. What is OLAP example?
6. Is OLAP a database?
7. What are the types of OLAP?
8. What are the functionalities of OLAP?
9. What are the storage models of OLAP?
10. What are cubes in data warehousing?
11. What is the heart of the Warehouse?
12. What is multidimensional OLAP?

What is roll-up in OLAP?

Roll-Up. The roll-up operation (also known as drill-up or aggregation operation) performs aggregation on a data cube, by climbing down concept hierarchies, i.e., dimension reduction. Roll-up is like zooming-out on the data cubes. Figure shows the result of roll-up operations performed on the dimension location.

What is rollup and drill down?

Drill-down refers to the process of viewing data at a level of increased detail, while roll-up refers to the process of viewing data with decreasing detail. Our system provides smooth and continuous level-of-detail control in all drilling operations.

What is slice and dice in data warehouse?

The main difference between slice and dice in data warehouse is that the slice is an operation that selects one specific dimension from a given data cube and provides a new subcube while the dice is an operation that selects two or more dimensions from a given data cube and provides a new subcube.

What is OLAP in database?

From Wikipedia, the free encyclopedia. Online analytical processing, or OLAP (/ˈoʊlæp/), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining.

What is OLAP example?

An OLAP Cube is a data structure that allows fast analysis of data according to the multiple Dimensions that define a business problem. A multidimensional cube for reporting sales might be, for example, composed of 7 Dimensions: Salesperson, Sales Amount, Region, Product, Region, Month, Year.

Is OLAP a database?

The core of most OLAP systems, the OLAP cube is an array-based multidimensional database that makes it possible to process and analyze multiple data dimensions much more quickly and efficiently than a traditional relational database.

What are the types of OLAP?

Types of OLAP Servers

• Relational OLAP (ROLAP)
• Multidimensional OLAP (MOLAP)
• Hybrid OLAP (HOLAP)
• Specialized SQL Servers.

What are the functionalities of OLAP?

The OLAP functions are grouped into these categories:

• Aggregate Functions.
• Analytic Functions.
• Hierarchical Functions.
• Lag Functions.
• OLAP DML Functions.
• Rank Functions.
• Share Functions.
• Window Functions.

What are the storage models of OLAP?

Microsoft SQL Server Analysis Services (SSAS) supports three main physical storage models for multidimensional platforms: multidimensional OLAP (MOLAP), relational OLAP (ROLAP), and hybrid OLAP (HOLAP). In practice, most SQL Server OLAP systems are implemented with the combination of these three storage models.

What are cubes in data warehousing?

Cubes are data processing units composed of fact tables and dimensions from the data warehouse. They provide multidimensional views of data, querying and analytical capabilities to clients. A cube can be stored on a single analysis server and then defined as a linked cube on other Analysis servers.

What is the heart of the Warehouse?

The answer is that the warehouse (heart) within the supply chain (body) is seen as a functional necessity that has to service the needs of the rest of the departments within the business (organs), whereas its own needs to operate properly are not considered as important and are often overlooked.

What is multidimensional OLAP?

Multidimensional OLAP (MOLAP) is a classical OLAP that facilitates data analysis by using a multidimensional data cube. Data is pre-computed, re-summarized, and stored in a MOLAP (a major difference from ROLAP). Using a MOLAP, a user can use multidimensional view data with different facets.