Question 1

Difference between ER Modeling and Dimensional Modeling.

Accepted Answer

Dimensional modelling is very flexible for the user perspective Dimensional data model is mapped for creating schemas Where as ER Model is not mapped for creating shemas and does not use in conversion of normalization of data into denormalized form ER Model is utilized for OLTP databases that uses any of the 1st or 2nd or 3rd normal forms, where as dimensional data model is used for data warehousing and uses 3rd normal form ER model contains normalized data where as Dimensional model contains denormalized data

Question 2

What is Data Mart?

Accepted Answer

Data Mart is a data repository which is served to a community of people who works on knowledge (also known as knowledge workers) The data resource can be from enterprise resources or from a data warehouse

Question 3

Explain the use of lookup tables and Aggregate tables.

Accepted Answer

At the time of updating the data warehouse, a lookup table is used When placed on the fact table or warehouse based upon the primary key of the target, the update is takes place only by allowing new records or updated records depending upon the condition of lookup The materialized views are aggregate tables It contains summarized data For example, to generate sales reports on weekly or monthly or yearly basis instead of daily basis of an application, the date values are aggregated into week values, week values are aggregated into month values and month values into year values To perform this process aggregate function is used

Question 4

What is data cleaning? How can we do that?

Accepted Answer

Data cleaning is also known as data scrubbing Data cleaning is a process which ensures the set of data is correct and accurate Data accuracy and consistency, data integration is checked during data cleaning Data cleaning can be applied for a set of records or multiple sets of data which need to be merged Data cleaning is performed by reading all records in a set and verifying their accuracy Typos and spelling errors are rectified Mislabeled data if available is labeled and filed Incomplete or missing entries are completed Unrecoverable records are purged, for not to take space and inefficient operations

Question 5

What is Bit Mapped Index?

Accepted Answer

Bitmap indexes make use of bit arrays (bitmaps) to answer queries by performing bitwise logical operations Bitmap indexes are useful in the data warehousing applications Bitmap indexes have a significant space and performance advantage over other structures for such data Tables that have less number of insert or update operations can be good candidates The advantages of Bitmap indexes are: - They have a highly compressed structure, making them fast to read - Their structure makes it possible for the system to combine multiple indexes together so that they can access the underlying table faster The Disadvantage of Bitmap indexes is: - The overhead on maintaining them is enormous

Question 6

What is the purpose of cluster analysis in Data Warehousing?

Accepted Answer

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 are 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

Question 7

What are the different models used in cluster analysis?

Accepted Answer

There are many algorithms that can be used to analyze the database to check the maintenance of all the data sets that are already present The different types of cluster models include as follows: - Connectivity models: these are the models that connect one cluster to another cluster This includes the example of hierarchical clustering that is based on the distance connectivity of one model to another model - Centroid models: these are the models that are used to find the clusters using the single mean vector It includes the example of k-means algorithm - Distribution models: it includes the specification of the models that are statistically distributed for example multivariate normal distribution model - Density models: deals with the clusters that are densely connected with one another in the regions having the data space - Group models: specifies the model that doesn’t provide the refined model for the output and just gives the grouping information

Question 8

What is Cascade and Drill Through? What is the difference between them?

Accepted Answer

Cascade: - Cascade process involves taking values from various other prompts - The result is a single report - The result is used when a criteria is to be implemented Drill Through: - Drill Through process is implemented when navigation from summary to detailed information - Drill Through has a parent and a child report - Data of another report can be seen based on the current details of data

Question 9

Explain about various caches available in Data Integrator

Accepted Answer

NO_CACHE – It is used for not caching values PRE_LOAD_CACHE – Result column preloads and compares the column into the memory, prior to executing the lookup PRE_LOAD_CACHE is used when the table can exactly fit in the memory space DEMAND_LOAD_CACHE – Result column loads and compares the column into the memory when a function performs the execution DEMAND_LOAD_CACHE is suitable while looking up the highly repetitive values with small subset of data

Question 10

What are the prime responsibilities of Data Integration Administrator?

Accepted Answer

- Scheduling and executing the batch jobs - Configuring, starting and stopping the real-time services - Adapters configuration and managing them - Repository usage, Job Server configuration - Access Server configuration - Batch job publishing - Real-time services publishing through web services

Question 11

What is Data Integration?

Accepted Answer

- The process of combining data from different resources - The combined data is provided to the users with unified view - Information from different enterprise domains are integrated – known as Enterprise Information Integration - Useful for merging information from different technologies among enterprises - The sub areas of data integration are 1 Data Warehousing 2 Data Migration 3 Master Data Management

Question 12

What are the benefits of data integration?

Accepted Answer

Following are the benefits of data integration: - Makes reporting, monitoring, placing customer information across the enterprise flexible and convenient - Data usage is efficient - Cost Effective - Risk adjusted profitability management as it allows accurate data extraction - Allows timely and reliable reporting, as data quality is the prime technology for business challenges

Question 13

What are the factors that are addressed to integrate data?

Accepted Answer

Following are the data integration factors: - Sub set of the available data should be optimal - Noise/distortion estimation levels because of sensory/processing conditions at the time of data collection - Accuracy, spatial and spectral resolution of data - Data formats, storage and retrieval mechanisms - Efficiency of computation for integrating data sets to reach the goals

Question 14

How do we measure progress in Data Integration?

Accepted Answer

Look for the existence of the following items: - Generic Data Models - An Enterprise Data Platform - Identify the Data Sources - Selection of a MDM Product - Implementation of a Customer Master Index or appropriate alternative

Question 15

What is Uniform Data Access Integration?

Accepted Answer

- UDAI places the data in the source systems - A set of views are defined for providing access the unified view to the clients / customers - Zero latency of data can be propagated from the source system - The generated consolidated data need not require separate storage space - Data history and version management is limited and applied only to the similar type of data - Accessing to the user data overloads on the source systems

Question 16

Describe about Physical Data Integration?

Accepted Answer

- Physical Data Integration is all about creating new system that replicates data from the source systems - This process is done to manage the data independent of the original system - Data Warehouse is the example of Physical Data Integration - The benefits of PDI include data version management, combination of data from various sources, like mainframes, flat files, databases - A separate system is needed for handling vast data volumes

Question 17

Which programming language was removed from the Visual Studio family when VB.net was released?

Accepted Answer

Visual Foxpro was part of Visual Studio 60 It was excluded in the Net version and was released as an independent programming language

Question 18

Why is code optimization important?

Accepted Answer

Optimized code tends to run faster and make more efficient use of the system’s resources Optimized codes are also less susceptible to errors and take lesser space in memory and in file size

Question 19

In Windows XP , what does the letter XP stands for?

Accepted Answer

The letters XP actually stands for eXPerience It was designed as an enhancement of Windows 2000, with a totally different and more attractive user interface/console

Question 20

What is the advantage of using ADO?

Accepted Answer

ADO or Active X Data objects, allows developers to create applications that can interoperate well with other data application services

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