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Phages of Data Acquisition in IBM Cognos

Phages in data acquisition:

  1. Data extraction
  2. Data transformation
  3. Data loading

Data extraction:

From various types of sources like RDBMS systems (oracle, SQL, server, tera data, sy base etc), files (txt, xml) and ERP systems like (SAP, people soft … etc)

Data transformation:

It is a process of transforming the data from one format to another format (client required format) by applying business lagiees

  • Data transformation is takes place in the staging area
  • Staging area is nothing but a temporary memory area where the transformation activity takes place
  • The following are transformation activity takes place in the staging area
  1. Data cleaning
  2. Data subbing
  3. Data merging
  4. Data aggregating

Data cleaning:

It is a process of converting inconsistent data (means UN uniform data ) in to consistent data (uniform data ) and removing un wanted data.

Customer (source) 

Cust no      cust f name               cust l name                   amt                        loc

1                           bill                         gates                           50000                  Newyork

2                           bill                         Clinton                       70000                  boston

3                           nara                      chandrababu            40000                  hyderabad

Customer target

Cust no                cust name                      amt        tax          loc

1                           billgates                            5000     500       Newyork

2                           billClinton                        7000    700        boston

3                          narachandrababu           4000     400       hyd

Screenshot_3

Staining area :

  1. Cust name= concat (Init cap (Cust name).’ ‘ , init cap(Cust name)
  2. Tax = actual

Data merging:

It is a process of combining multiple sources into a single target (single output) (or) it is a process combining multiple input flows into a single output flow there are two types of data merging

  1. union
  2. join

Union:

It is a process of combining multiple sources which are having same structure (number of columns should be same and the data types of the corresponding columns should be same)

  • sources can be homogeneous (same type of sources) or heterogeneous (default types of sources)

Screenshot_5

Join:

To perform join, there should be at least one common column between the sources, sources can be homogeneous (or) hetero genius.

Ex: source 1

Screenshot_6

Data aggregation:

  It is a process of converting the details data in to summary data by applying group functions like sum, max, min, avg, count.

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  • It s a process of performing group calculations like sum, max min, avg , etc…

Screenshot_7

Data loading:

It is a process of populating (or) dumping the source data (OLTP) into the target system (DWH) there are 2 types of data loading

  1. initial load (or) full load
  2. incremental load (or) delta load

Initial load:

Leading the data for the first time from source to target is called initial load (or) full load

Incremental load:

It is a process of inserting new records and updating existing records when coming with new values

Data mart:

It is a subset of data ware house (or) it is a subject oriented database to support middle level management (or) it is a high

Screenshot_8

There are two approaches to design the data mart

  • top-down approach (W.H inman):

Screenshot_9

  • bottom-up approach(Ralph Kimball):

Screenshot_10

  • based on the design, data marts are categorized into two types
  1. dependant data mart
  2. independent data mart
  • Data mart in to down approach is dependent. Because designing of these data marts depends upon design of enterprise data mart
  • Data mart bottom approach is independent. Because designing of these data mart doesn’t depend upon enterprise data mart.

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