Most frequently Asked OLAP Interview questions and Answers for freshers and experienced pdf free download
1) Explain about OLAP ?
OLAP is known as online analytical processing which provides answers to queries which are multi dimensional in nature. It composes relational reporting and data mining for providing solutions to business intelligence. This term OLAP is created from the term OLTP.
2) Explain about the functionality of OLAP?
Hyper cube or multidimensional cube forms the core of OLAP system. This consists of measures which are arranged according to dimensions. Hyper cube Meta data is created by star or snow flake schema of tables in RDBMS. Dimensions are extracted from dimension table and measures from the fact table.
3) Explain about MOLAP?
Classic form of OLAP is known as MOLAP and it is often called as OLAP. Simple database structures such as time period, product, location, etc are used. Functioning of each and every dimension or data structure is defined by one or more hierarchies.
4) Explain about ROLAP?
Functioning of ROLAP occurs simultaneously with relational databases. Data and tables are stored as relational tables. To hold new information or data new tables are created. Functioning of ROLAP depends upon specialized schema design.
5) Explain about aggregations?
OLAP can process complex queries and give the output in less than 0.1 seconds, for it to achieve such a performance OLAP uses aggregations. Aggregations are built by aggregating and changing the data along the dimensions. Possible combination of aggregations can be determined by the combination possibilities of dimension granularities.
6) Explain about the view selection problem?
Often calculating all the data is not possible by aggregations for this reason some of the complex data problems are solved. In order to determine which data should be solved and calculated, developers use View selection application. This solution is often used to reduce calculation problem.
7) Explain about the role of bitmap indexes to solve aggregation problems?
Bitmaps are very useful in start schema to join large databases to small databases. Answer queries and bit arrays are used to perform logical operations on the databases. Bit map indexes are very efficient in handling Gender differentiation; also repetitive tasks are performed with much larger efficiency.
8) Explain about Encoding technique used in bitmaps indexes?
Bitmaps commonly use one bitmap for every single distinct value. Number of bitmaps used can be reduced by opting for a different type of encoding. Space can be optimized but when a query is generated bitmaps have to be accessed.
9) Explain about Binning?
Binning process is very useful to save space. Performance may vary depending upon the query generated sometimes solution to a query can come within few seconds and sometimes it may take longer time. Binning process holds multiple values in the same bin.
10) Explain about candidate check?
The process which is underlined during the check of base data is known as candidate check. When performing candidate check performance varies either towards the positive side or to the negative side. Performance of candidate check depends upon the user query and also they examine the base data.
11) Explain about Hybrid OLAP?
When a database developer uses Hybrid OLAP it divides the data between relational and specialized storage. In some particular modifications a HOLAP database may store huge amounts of data in its relational tables. Specialized data storage is used to store data which is less detailed and more aggregate.
12) Explain about API`s of OLAP?
Microsoft in the late 1997 introduced a standard API known as OLE DB. After which XML was used for analysis specification and this specification was largely used by many vendors throughout the world as a standard specification. MDX is the standards specification for OLAP.
13) 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.
14) Explain about analysis?
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.
15) 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.
16) 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.
17) 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.
18) Explain about the functionality of OLAP?
Hyper cube or multidimensional cube forms the core of OLAP system. This consists of measures which are arranged according to dimensions. Hyper cube Meta data is created by star or snow flake schema of tables in RDBMS. Dimensions are extracted from dimension table and measures from the fact table.
19) Explain about the view selection problem?
Often calculating all the data is not possible by aggregations for this reason some of the complex data problems are solved. In order to determine which data should be solved and calculated, developers use View selection application. This solution is often used to reduce calculation problem.
20) Compare Data Warehouse database and OLTP database.
Data Warehouse is used for business measures cannot be used to cater real time business needs of the organizationand is optimized for lot of data, unpredictable queries. On the other hand, OLTP database is for real time business operations that are used for a common set of transactions. Data warehouse does not require any validation of data. OLTP database requires validation of data
1) Explain about OLAP ?
OLAP is known as online analytical processing which provides answers to queries which are multi dimensional in nature. It composes relational reporting and data mining for providing solutions to business intelligence. This term OLAP is created from the term OLTP.
2) Explain about the functionality of OLAP?
Hyper cube or multidimensional cube forms the core of OLAP system. This consists of measures which are arranged according to dimensions. Hyper cube Meta data is created by star or snow flake schema of tables in RDBMS. Dimensions are extracted from dimension table and measures from the fact table.
3) Explain about MOLAP?
Classic form of OLAP is known as MOLAP and it is often called as OLAP. Simple database structures such as time period, product, location, etc are used. Functioning of each and every dimension or data structure is defined by one or more hierarchies.
4) Explain about ROLAP?
Functioning of ROLAP occurs simultaneously with relational databases. Data and tables are stored as relational tables. To hold new information or data new tables are created. Functioning of ROLAP depends upon specialized schema design.
5) Explain about aggregations?
OLAP can process complex queries and give the output in less than 0.1 seconds, for it to achieve such a performance OLAP uses aggregations. Aggregations are built by aggregating and changing the data along the dimensions. Possible combination of aggregations can be determined by the combination possibilities of dimension granularities.
6) Explain about the view selection problem?
Often calculating all the data is not possible by aggregations for this reason some of the complex data problems are solved. In order to determine which data should be solved and calculated, developers use View selection application. This solution is often used to reduce calculation problem.
7) Explain about the role of bitmap indexes to solve aggregation problems?
Bitmaps are very useful in start schema to join large databases to small databases. Answer queries and bit arrays are used to perform logical operations on the databases. Bit map indexes are very efficient in handling Gender differentiation; also repetitive tasks are performed with much larger efficiency.
8) Explain about Encoding technique used in bitmaps indexes?
Bitmaps commonly use one bitmap for every single distinct value. Number of bitmaps used can be reduced by opting for a different type of encoding. Space can be optimized but when a query is generated bitmaps have to be accessed.
9) Explain about Binning?
Binning process is very useful to save space. Performance may vary depending upon the query generated sometimes solution to a query can come within few seconds and sometimes it may take longer time. Binning process holds multiple values in the same bin.
10) Explain about candidate check?
The process which is underlined during the check of base data is known as candidate check. When performing candidate check performance varies either towards the positive side or to the negative side. Performance of candidate check depends upon the user query and also they examine the base data.
11) Explain about Hybrid OLAP?
When a database developer uses Hybrid OLAP it divides the data between relational and specialized storage. In some particular modifications a HOLAP database may store huge amounts of data in its relational tables. Specialized data storage is used to store data which is less detailed and more aggregate.
12) Explain about API`s of OLAP?
Microsoft in the late 1997 introduced a standard API known as OLE DB. After which XML was used for analysis specification and this specification was largely used by many vendors throughout the world as a standard specification. MDX is the standards specification for OLAP.
13) 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.
14) Explain about analysis?
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.
15) 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.
16) 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.
17) 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.
18) Explain about the functionality of OLAP?
Hyper cube or multidimensional cube forms the core of OLAP system. This consists of measures which are arranged according to dimensions. Hyper cube Meta data is created by star or snow flake schema of tables in RDBMS. Dimensions are extracted from dimension table and measures from the fact table.
19) Explain about the view selection problem?
Often calculating all the data is not possible by aggregations for this reason some of the complex data problems are solved. In order to determine which data should be solved and calculated, developers use View selection application. This solution is often used to reduce calculation problem.
20) Compare Data Warehouse database and OLTP database.
Data Warehouse is used for business measures cannot be used to cater real time business needs of the organizationand is optimized for lot of data, unpredictable queries. On the other hand, OLTP database is for real time business operations that are used for a common set of transactions. Data warehouse does not require any validation of data. OLTP database requires validation of data
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