• USA : +1 973 910 5725
  • INDIA: +91 905 291 3388
  • info@tekslate.com
  • Login

DataWarehousing Fundamentals

 

 

1

 

 

ETL Tool

E – Extract 2setting the data

T-transform2doing Intermediate operation

L-Load2Load to destination

 

Tools

Data stage, Informatica, AB-Initio, SSIS, OWB et

 

Analytical tool

To create multi – Dimensional object and object and provides supports for multi –Dimensional analysis

 

Tools

 COGNOS, BO, Hyperion, SSAS, Micro strategy, OBIEE etc.

 

Reporting tools

To display the data in the understand and required format, we go for this,

 

Tools

COGNOS, BO, SSRS, Hyperion, Micro strategy B Crstal on  OBIEE etc.

 

Inclined to build a profession as Teradata Developer? Then here is the blog post on
 Online Teradata Training.

It is composed on observable and recordable facts, that are off be found in transaction(or)operation system

 

Information

 It is an integrated collection of facts and  is used as the[organized – data is called information] bases for decision making

 

Need of dataware housing

To have single version of data, in single storage

To complete with other organization market

To analysis tactical strategic queries etc.

Definition of ODS, DWH, BI, OLTP, OLAP

QLTP

 On line transaction processing

Here day to day operations data available (immediate operation data) Here all the DML operation can be performed.

ODS(Operational data store)

It is data stag structure that acts like repository for near real time operational data rather than long trand data.

This ODS may for them become to enterprise operational database(or) stage area to data were house

DWH(Data were house)

It is data base structure, where huge data store, so that we can take appropriate decision

OLAP(Online Analytical processing)

It is an application that collects managing and present multi– dimensional data analysis and management purpose.

BI(Business Intelligence)

BI retrieve the data from data warehouse to make business decision and management(it can takes the  help OLAP)

Data warehouse Definition

There are many authors founder define different approaches

INMON

SEAM KELLY etc.

 

INMON

Some people calling INMON father of data ware house

A Data ware house is subject oriented

Integrated.

Time variant

Non-volatile, Data Granularity

Collection or data, in this support of

Decision making

SEAM KELLY

A Data warehouse is subject oriented, integrated, Non- volatile, time variant, separate collection of data

 

Subject Oriented

The data in data ware house should belong to a specific subject Area, Domain (or) Business

 

Example

Entire banking, Information in single place Entire medias information in single place

 

Integrated

By loading the data we need follows standardized mechanism, we have single management data

 

Example

Naming conversion, coding measurement, data attribute etc.

 

Non – volatile

Data in the data were house data, should not updata and delete.

 

Time variant

The data should be store based on time frame so that, we cab current month sales, what is

 

Previous month

sales, what could be sales of future month

Check out the top Teradata Interview Questions now!

Separate

 Where  have should be separate traditional system

 

Accessible

Where have should be high available etc.

 

Data Warehousing life cycle

It is combination of 3 life cycles creating a data base and modeling database.

ETL requirement gathering

ETL Analysis

ETL Design

ETL Coding

ETL Testing

ETL deployment and maintenance

Analytical life cycle

Requirement gathering analysis

Designing the objects

Create multi-dimensional object

Testing multi- dimensional object

Deployment implement

Reporting life cycle

Reporting Testing

Reporting Design

Reporting Coding

Reporting Publishers And maintenance.

For Indepth knowledge on Teradata click on:
Summary
Review Date
Reviewed Item
DataWarehousing Fundamentals
Author Rating
5

“At TekSlate, we are trying to create high quality tutorials and articles, if you think any information is incorrect or want to add anything to the article, please feel free to get in touch with us at info@tekslate.com, we will update the article in 24 hours.”

0 Responses on DataWarehousing Fundamentals"

Leave a Message

Your email address will not be published. Required fields are marked *

Site Disclaimer, Copyright © 2016 - All Rights Reserved.