Sunday, 1 June 2014

IF7203-DATA WAREHOUSING AND DATA MINING QUESTION BANK WITH ANSWERS UNIT I-DATA WAREHOUSE

Part A
Two marks
1.  Define Data warehouse (or) what is Data Warehouse?
A data warehouse is a repository of multiple heterogeneous data sources organized under a unified schema at a single site to facilitate management decision making.                          (Or)
A data warehouse is a subject-oriented, time-variant and non-volatile collection of data in support of management’s decision-making process.
2.  What are operational databases?
Organizations maintain large database that are updated by daily transactions are called operational databases.
3.  Define OLTP?
If an on-line operational database systems is used for efficient retrieval, efficient storage and management of large amounts of data, then the system is said to be on-line transaction processing.
4.  Define OLAP?
Data warehouse systems serves users (or) knowledge workers in the role of data analysis and decision-making. Such systems can organize and present data in various formats. These systems are known as on-line analytical processing systems.
5.  Write short notes on multidimensional data model?
Data warehouses and OLTP tools are based on a multidimensional data model. This model is used for the design of corporate data warehouses and department data marts. This model contains a Star schema, Snowflake schema and Fact constellation schemas. The core of the multidimensional model is the data cube.
6.  Define data cube?
It consists of a large set of facts (or) measures and a number of dimensions.
7.  What are facts?
Facts are numerical measures. Facts can also be considered as quantities by which we can analyze the relationship between dimensions.
8.  What are dimensions?
Dimensions are the entities (or) perspectives with respect to an organization for keeping records and are hierarchical in nature.
9.  Define dimension table?
A dimension table is used for describing the dimension. (e.g.) A dimension table for item may contain the attributes item_ name, brand and type.
10.       Define fact table?
Fact table contains the name of facts (or) measures as well as keys to each of the related dimensional tables.
11.       What are lattice of cuboids?
In data warehousing research literature, a cube can also be called as cuboids. For different (or) set of dimensions, we can construct a lattice of cuboids, each showing the data at different level. The lattice of cuboids is also referred to as data cube.
12.       What are apex cuboids?
The 0-D cuboids which holds the highest level of summarization is called the apex cuboids. The apex cuboids are typically denoted by all.
13.       List out the components of star schema?
A large central table (fact table) containing the bulk of data with no redundancy. A set of smaller attendant tables (dimension tables), one for each dimension.
14.       What is snowflake schema?
The snowflake schema is a variant of the star schema model, where some dimension tables are normalized thereby further splitting the tables in to additional tables.
15.       List out the components of fact constellation schema?
This requires multiple fact tables to share dimension tables. This kind of schema can be viewed as a collection of stars and hence it is known as galaxy schema (or) fact constellation schema.
16.       Point out the major difference between the star schema and the snowflake schema?
The dimension table of the snowflake schema model may be kept in normalized form to reduce redundancies. Such a table is easy to maintain and saves storage space.
17.       Which is popular in the data warehouse design, star schema model (or) snowflake schema model?
Star schema model, because the snowflake structure can reduce the effectiveness and more joins will be needed to execute a query.
18.       Define concept hierarchy?
A concept hierarchy defines a sequence of mappings from a set of low-level concepts to higher-level concepts.
19.       Define total order?
If the attributes of a dimension which forms a concept hierarchy such as “street<city< province_or_state <country”, then it is said to be total order. Country Province or state City Street Fig: Partial order for location
20.       Define partial order?
If the attributes of a dimension which forms a lattice such as “day<{month<quarter; week}<year, then it is said to be partial order.
21.       Define schema hierarchy?
A concept hierarchy that is a total (or) partial order among attributes in a database schema is called a schema hierarchy.
22.       List out the OLAP operations in multidimensional data model?
Roll-up _ Drill-down _ Slice and dice _ Pivot (or) rotate
23.       What is roll-up operation?
The roll-up operation is also called drill-up operation which performs aggregation on a data cube either by climbing up a concept hierarchy for a dimension (or) by dimension reduction.
24.       What is drill-down operation?
Drill-down is the reverse of roll-up operation. It navigates from less detailed data to more detailed data. Drill-down operation can be taken place by stepping down a concept hierarchy for a dimension.
25.       What is slice operation?
The slice operation performs a selection on one dimension of the cube resulting in a sub cube.
26.       What is dice operation?
The dice operation defines a sub cube by performing a selection on two (or) more dimensions.
27.       What is pivot operation?
This is a visualization operation that rotates the data axes in an alternative presentation of the data.
28.       List out the views in the design of a data warehouse?
Top-down view _ Data source view _ Data warehouse view _ Business query view.
29.       What are the methods for developing large software systems?
Waterfall method _ Spiral method
30.       How the operation is performed in waterfall method?
The waterfall method performs a structured and systematic analysis at each step before proceeding to the next, which is like a waterfall falling from one step to the next.
31.       How the operation is performed in spiral method?
The spiral method involves the rapid generation of increasingly functional systems, with short intervals between successive releases. This is considered as a good choice for the data warehouse development especially for data marts, because the turnaround time is short, modifications can be done quickly and new designs and technologies can be adapted in a timely manner.
32.       List out the steps of the data warehouse design process?
Choose a business process to model.
 Choose the grain of the business process
 Choose the dimensions that will apply to each fact table record.
 Choose the measures that will populate each fact table record.
33.       What is enterprise warehouse?
An enterprise warehouse collects all the information’s about subjects spanning the entire organization. It provides corporate-wide data integration, usually from one (or) more operational systems (or) external information providers. It contains detailed data as well as summarized data and can range in size from a few giga bytes to hundreds of giga bytes, tera bytes (or) beyond.
34.       What is data mart?
Data mart is a database that contains a subset of data present in a data warehouse. Data marts are created to structure the data in a data warehouse according to issues such as hardware platforms and access control strategies. We can divide a data warehouse into data marts after the data warehouse has been created. Data marts are usually implemented on low-cost departmental servers that are UNIX (or) windows/NT based.
35.       What are dependent and independent data marts?
Dependent data marts are sourced directly from enterprise data warehouses. Independent data marts are data captured from one (or) more operational systems (or) external information providers (or) data generated locally with in particular department (or) geographic area.
 36.       What is virtual warehouse?
 A virtual warehouse is a set of views over operational databases. For efficient query processing, only some of the possible summary views may be materialized. A virtual warehouse is easy to build but requires excess capability on operational database servers.
37.       Define indexing?
 Indexing is a technique, which is used for efficient data retrieval (or) accessing data in a faster manner. When a table grows in volume, the indexes also increase in size requiring more storage.
38.       What are the types of indexing?
B-Tree indexing _ Bit map indexing _ Join indexing
39.       Define metadata?
Metadata is used in data warehouse is used for describing data about data. (i.e.) Meta data are the data that define warehouse objects. Metadata are created for the data names and definitions of the given warehouse.
40.       Define VLDB?
Very Large Data Base. If a database whose size is greater than 100GB, then the database is said to be very large database.
PART B
16 (OR) 8 MARKS
1.      Discuss the components of data warehouse.    (8)
_Subject-oriented
_Integrated
_Time-Variant
_Non-volatile
2.      List out the differences between OLTP and OLAP.      (8)
_ Users and system orientation
_ Data contents
_ Database design
_ View
_ Access patterns
3.       Discuss the various schematic representations in multidimensional model.
_ Star schema
_ Snow flake schema
_ Fact constellation schema



4.       Explain the OLAP operations I multidimensional model.
_ Roll-up
_ Drill-down
_ Slice and dice
_ Pivot or rotate
5.      Explain the design and construction of a data warehouse.
_ Design of a data warehouse
• Top-down view
• Data source view
• Data warehouse view
• Business query view
_ Process of data warehouse design
6.      Explain the three-tier data warehouse architecture.
_ Warehouse database server (Bottom tier)
_ OLAP server (middle tier)
_ Client (top tier)
7.      Explain indexing.
_ Definition
_ B-Tree indexing
_ Bit-map indexing
_ Join indexing
8.       Write notes on metadata repository.
_ Definition
_ Structure of the data warehouse
_ Operational metadata
_ Algorithms used for summarization
_ Mapping from operational environment to data warehouse
_ Data related to system performance
_ Business metadata

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