1⟩ Explain me what kind of costs are involved in Data Marting?
Data Marting involves hardware & software cost, network access cost, and time cost.
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2⟩ Tell us out of star schema and snowflake schema, whose dimension table is normalized?
Snowflake schema uses the concept of normalization.
3⟩ Tell us what is Virtual Warehouse?
The view over an operational data warehouse is known as virtual warehouse.
4⟩ Tell us what does the Query Manager responsible for?
Query Manager is responsible for directing the queries to the suitable tables.
5⟩ Can you list the Schema that a data warehouse system can implements?
A data Warehouse can implement star schema, snowflake schema, and fact constellation schema.
6⟩ Tell us what is the main difference between Inmon and Kimball philosophies of data warehousing?
Both differ in the concept of building the data warehouse.
☛ Kimball views data warehousing as a constituency of Data marts. Data marts are focused on delivering business objectives for departments in the organization. And the data warehouse is a conformed dimension of the data marts. Hence, a unified view of the enterprise can be obtained from the dimension modeling on a local departmental level.
☛ Inmon explains in creating a data warehouse on a subject-by-subject area basis. Hence, the development of the data warehouse can start with data from the online store. Other subject areas can be added to the data warehouse as their needs arise. Point-of-sale (POS) data can be added later if management decides it is necessary.
☛ Hence, Kimball–First Data Marts–Combined way —Data warehouse
☛ Inmon—First Data warehouse–Later—-Data marts
7⟩ Tell us what is Hybrid SCD?
Hybrid SCDs are a combination of both SCD 1 and SCD 2.
It may happen that in a table, some columns are important and we need to track changes for them i.e., capture the historical data for them whereas in some columns even if the data changes, we do not have to bother.
For such tables, we implement Hybrid SCDs, where in some columns are Type 1 and some are Type 2.
8⟩ Explain me why is chameleon method used in data warehousing?
Chameleon is a hierarchical clustering algorithm that overcomes the limitations of the existing models and the methods present in the data warehousing. This method operates on the sparse graph having nodes: that represent the data items, and edges: representing the weights of the data items.
This representation allows large dataset to be created and operated successfully. The method finds the clusters that are used in the dataset using two phase algorithm.
☛ The first phase consists of the graph partitioning that allows the clustering of the data items into large number of sub-clusters.
☛ Second phase uses an agglomerative hierarchical clustering algorithm to search for the clusters that are genuine and can be combined together with the sub-clusters that are produced.
9⟩ Tell us what do OLAP and OLTP stand for?
OLAP is an acronym for Online Analytical Processing and OLTP is an acronym of Online Transactional Processing.
10⟩ Please explain what is VLDB?
A very large database, or VLDB, is a database that contains an extremely large number of tuples (database rows), or occupies an extremely large physical file system storage space. A one terabyte database would normally be considered to be a VLDB.
11⟩ Tell us what is snapshot with reference to data warehouse?
☛ Snapshot refers to a complete visualization of data at the time of extraction. It occupies less space and can be used to back up and restore data quickly.
☛ A snapshot is a process of knowing about the activities performed. It is stored in a report format from a specific catalog. The report is generated soon after the catalog is disconnected.
12⟩ Explain what are the reasons for partitioning?
Partitioning is done for various reasons such as easy management, to assist backup recovery, to enhance performance.
13⟩ Tell me do you know what is Normalization?
Normalization splits up the data into additional tables.
14⟩ Can you define dimension?
The dimensions are the entities with respect to which an enterprise keeps the records.
15⟩ Tell us what is Summary Information?
Summary Information is the area in data warehouse where the predefined aggregations are kept.
16⟩ Explain me what is the purpose of cluster analysis in Data Warehousing?
Cluster analysis is used to define the object without giving the class label. It analyzes all the data that is present in the data warehouse and compare the cluster with the cluster that is already running. It performs the task of assigning some set of objects into the groups also known as clusters. It is used to perform the data mining job using the technique like statistical data analysis. It includes all the information and knowledge around many fields like machine learning, pattern recognition, image analysis and bio-informatics. Cluster analysis performs the iterative process of knowledge discovery and includes trials and failures. It is used with the pre-processing and other parameters as a result to achieve the properties that are desired to be used.
Purpose of cluster analysis :-
☛ Scalability
☛ Ability to deal with different kinds of attributes
☛ Discovery of clusters with attribute shape
☛ High dimensionality
☛ Ability to deal with noisy
☛ Interpretability
17⟩ Explain me what is junk dimension?
☛ In scenarios where certain data may not be appropriate to store in the schema, this data (or attributes) can be stored in a junk dimension. The nature of data of junk dimension is usually Boolean or flag values.
☛ A single dimension is formed by lumping a number of small dimensions. This dimension is called a junk dimension. Junk dimension has unrelated attributes. The process of grouping random flags and text attributes in dimension by transmitting them to a distinguished sub dimension is related to junk dimension.
18⟩ What is the types of OLAP server?
There are four types of OLAP servers, namely Relational OLAP, Multidimensional OLAP, Hybrid OLAP, and Specialized SQL Servers.
19⟩ Tell me the process that are involved in Data Warehousing?
Data Warehousing involves data cleaning, data integration and data consolidations.
20⟩ Can you tell us what is data mart?
Data mart contains the subset of organization-wide data. This subset of data is valuable to specific groups of an organization. In other words, we can say that a data mart contains data specific to a particular group.
