Concept explainers
a. Definition of data warehouse.
Explanation of Solution
Data warehouse is a large collection of data which is further used by companies for decision making process of management. The data collection is subject-oriented, integrated, time-variant and non-updateable.
b. Definition of data mart.
Explanation of Solution
Data mart: A data warehouse which is limited in scope is called data mart. The data stored in data warehouse is selected and summarized using extract, transform and load process.
c. Definition of reconciled data.
Explanation of Solution
Reconciled data: It is detailed and current data which act as single source for all decision support system. This type of data is stored for enterprise data warehouse and operational data store.
d. Definition of derived data.
Explanation of Solution
Derived data: Data which is being extracted, formatted and segregated for end-user decision support application is known as derived data.
e. Definition of enterprise data warehouse.
Explanation of Solution
Enterprise data warehouse: It is a centralized, integrated data warehouse which act as the control point and only source for all data which is being made available to end user for decision making.
f. Definition of real-time data warehouse.
Explanation of Solution
Real-time data warehouse: It is a type of data warehouse which stores data related to transaction in near real time feeds from system of records. It can analyze data and control business rules in near real time so that appropriate actions can be taken as per current business events. It typically stores moderate size
g. Definition of star schema.
Explanation of Solution
Star schema: It is a database design where in dimensional data is separated from fact or event data. It is simplest type of data warehouse schema. It is called star schema as it is in the shape of start and is similar to relational model where fact table is represented at the centre and multiple dimensional table are connected to the centre fact table.
h. Definition of snowflake schema.
Explanation of Solution
Snowflake schema: It is an extension to star schema where dimensional tables are normalized into several related tables. Normalization of dimensional tables splits this table into multiple tables and the schema diagram resembles that of snowflake.
i. Definition of grain.
Explanation of Solution
Grain: Grain is the description of level of details for a fact table. For example, suppose a fact table stores information related to sales of specific product in various locations on a daily basis. Then grain for this fact table will be “information of product sale by location and by day”
j. Definition of conformed dimension.
Explanation of Solution
Conformed dimension: It is a dimension in which multiple dimension tables which are associated with multiple fact tables has same business meaning and primary key with each fact table.
k. Definition of static extract.
Explanation of Solution
Static extractis a type of data extractionmethod used to capture a snapshot of required source of data at a point of time. It is used to fill the data warehouse during initial phases.
l. Definition of incremental extract.
Explanation of Solution
Incremental extract is also a type of data extraction method which captures only the changes that have occurred in the source data since the last capture. It is used for ongoing warehouse maintenance.
m. Definition of refresh mode.
Explanation of Solution
Refresh modeis a strategy used for filling the data warehouse with data where bulk rewriting of the target data is involved at periodic intervals. Target data are filled in data warehouse initially and then rewritten periodically by replacing the previous content.
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Chapter 9 Solutions
Modern Database Management
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