OLAP is an acronym for Online Analytical Processing. OLAP performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling.
A data cube stores data in a summarized version which helps in a faster analysis of data. The data is stored in such a way that it allows reporting easily. E.g. using a data cube a user may want to analyze weekly, monthly performance of an employee. Here, month and week could be considered as the dimensions of the cube.
3. Where is Data Sources in OLAP?
Data source is where the data comes from in data warehousing. The data collected from various sources and is cleaned. The data source can be internal or external. Efficient Analysis and cleansing of source data is the key success to data warehousing.
Data in a warehouse comes from the transactions. Fact table in a data warehouse consists of facts and/or measures. The nature of data in a fact table is usually numerical. e.g. If I want to know the number of resources used for a task, my fact table will store the actual measure (of resources) while my Dimension table will store the task and resource details.
5. What are Database roles in OLAP?
Database level roles are used to manage the security of the database. The role can be either fixed or flexible. Fixed roles are predefined while flexible roles can be created. Examples of some fixed database level roles are db_owner, db_securityadmin, db_datawriter etc.
a) Multidimensional
Explanation:
Given a relation used for data analysis, we can identify some of its attributes as measure attributes, since they measure some value, and can be aggregated upon.Dimension attribute define the dimensions on which measure attributes, and summaries of measure attributes, are viewed.
d) DECODE (expression, search, result [, search, result]… [, default])
b) 4
Explanation:
{ (item name, color, clothes size), (item name, color), (item name), () }.
9. What do data warehouses support?
a) OLAP
b) OLTP
c) OLAP and OLTP
d) Operational databases
a) OLAP
d) None of the mentioned
Explanation:
'Group by cube' is used .
11. In SQL the cross-tabs are created using:
a) Slice
b) Dice
c) Pivot
d) All of the mentioned
a) Slice
Explanation:
pivot (sum(quantity) for color in ('dark','pastel','white')).
a) Roll-up
Explanation:
The opposite operation-that of moving from coarser-granularity data to finer-granularity data-is called a drill down.
d) Both a and b
Explanation:
For eg., The item name and colour is viewed for a fixed size.
a) Two dimensional cube
Explanation:
Each cell in the cube is identified for the values for the three dimensional attributes.
a) Online analytical processing
Explanation:
OLAP is the manipulation of information to support decision making.
c) Both a and b
24. The output of an OLAP query is displayed as a:
a) Matrix
b) Pivot
c) Both a and b
d) excel
c) Both a and b
a) Multidimensional
d) All of the above
a) A condition when each cell of the cube is filled with data and that leads to more processing time.
d) Both 1 and 2
d) All of the above
31. What are the different industries which use this marketing tool?
Many different companies can use this tool for developing their business strategy but it is often three major industries which use this tool more. Those three industries are Consumer goods industries, Retail industries, and financial services industry. These industry`s have huge amount of data in their disposal which makes then to use these tools to determine their exact customer.
32. Explain about the database marketing application of OLAP?
Database marketing tool or application helps a user or marketing professional in determining the right tool or strategy for his valuable add campaign. This tool collects data from all sources and gives relevant information the specialist with their add campaign. It gives a complete picture to the developer.
33. Explain about multidimensional features present in OLAP?
Multidimensional support is very essential if we are to include multiple hierarchies in our data analysis. Multidimensional feature allows a user to analyze business and organization. OLAP efficiently handles support for multidimensional features.
Analysis defines about the logical and statistical analysis required for an efficient output. This involves writing of code and performing calculations, but most part of these languages does not require complex programming language knowledge. There are many specific features which are included such as time analysis, currency translation, etc.
35. Explain about shared features of OLAP?
Shared implements most of the security features into OLAP. If multiple accesses are required admin can make necessary changes. The default security level for all OLAP products is read only. For multiple updates it is predominant to make necessary security changes.