Answer: A Data Warehouse is a collection of data marts representing historical data from different operational data source (OLTP). The data from these OLTP are structured and optimized for querying and data analysis in a Data Warehouse.
Question.2 What is a Data mart?
Answer: A Data Mart is a subset of a data warehouse that can provide data for reporting and analysis on a section, unit or a department like Sales Dept, HR Dept, etc. The Data Mart are sometimes also called as HPQS (Higher Performance Query Structure).
Question.3 What is OLAP?
Answer: OLAP stands for Online Analytical Processing. It uses database tables (Fact and Dimension tables) to enable multidimensional viewing, analysis and querying of large amount of data.
Question.4 What is OLTP?
Answer: OLTP stands for Online Transaction Processing Except data warehouse databases the other databases are OLTPs. These OLTP uses normalized schema structure. These OLTP databases are designed for recording the daily operations and transactions of a business.
Question.5 What are Dimensions?
Answer: Dimensions are categories by which summarized data can be viewed. For example a profit Fact table can be viewed by a time dimension.
Question.6 What are Confirmed Dimensions?
Answer: The Dimensions which are reusable and fixed in nature Example customer, time, geography dimensions.
Question.7 What are Fact Tables?
Answer: A Fact Table is a table that contains summarized numerical (facts) and historical data. This Fact Table has a foreign key-primary key relation with a dimension table. The Fact Table maintains the information in 3rd normal form.
A star schema is defined is defined as a logical database design in which there will be a centrally located fact table which is surrounded by at least one or more dimension tables. This design is best suited for Data Warehouse or Data Mart.
Question.8 What are the types of Facts?
Answer: The types of Facts are as follows.
1. Additive Facts: A Fact which can be summed up for any of the dimension available in the fact table.
2. Semi-Additive Facts: A Fact which can be summed up to a few dimensions and not for all dimensions available in the fact table.
3. Non-Additive Fact: A Fact which cannot be summed up for any of the dimensions available in the fact table.
Question.9 What are the types of Fact Tables?
Answer: The types of Fact Tables are:
1. Cumulative Fact Table: This type of fact tables generally describes what was happened over the period of time. They contain additive facts.
2. Snapshot Fact Table: This type of fact table deals with the particular period of time. They contain non-additive and semi-additive facts.
Question.10 What is Grain of Fact?
Answer: The Grain of Fact is defined as the level at which the fact information is stored in a fact table. This is also called as Fact Granularity or Fact Event Level.
Question.11 What is Factless Fact table?
Answer: The Fact Table which does not contains facts is called as Fact Table. Generally when we need to combine two data marts, then one data mart will have a fact less fact table and other one with common fact table.
Question.12 What are Measures?
Answer: Measures are numeric data based on columns in a fact table.
Question.13 What are Cubes?
Answer: Cubes are data processing units composed of fact tables and dimensions from the data warehouse. They provided multidimensional analysis.
Question.14 What are Virtual Cubes?
Answer: These are combination of one or more real cubes and require no disk space to store them. They store only definition and not the data.
Question.15 What is a Star schema design?
Answer: A Star schema is defined as a logical database design in which there will be a centrally located fact table which is surrounded by at least one or more dimension tables. This design is best suited for Data Warehouse or Data Mart.
Question.16 What is Snow Flake schema Design?
Answer: In a Snow Flake design the dimension table (de-normalized table) will be further divided into one or more dimensions (normalized tables) to organize the information in a better structural format. To design snow flake we should first design star schema design.
Question.17 What is Operational Data Store [ODS] ?
Answer: It is a collection of integrated databases designed to support operational monitoring. Unlike the OLTP databases, the data in the ODS are integrated, subject oriented and enterprise wide data.
Question.18 What is Denormalization?
Answer: Denormalization means a table with multi duplicate key. The dimension table follows Denormalization method with the technique of surrogate key.
Question.19 What is Surrogate Key?
Answer: A Surrogate Key is a sequence generated key which is assigned to be a primary key in the system (table).
