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Showing posts with label difference. Show all posts
Showing posts with label difference. Show all posts

Wednesday, October 01, 2014

Difference Between Normal Lookup and Sparse Lookup


Normal Lookup :-
  • Normal Lookup data needs to be in memory
  • Normal might provide poor performance if the reference data is huge as it has to put all the data in memory.
  • Normal Lookup can have more than one reference link.
  • Normal lookup can be used with any database

Friday, October 11, 2013

Difference between OLTP and OLAP


OLTP:
Online Transactional Processing databases are functional orientated, they are designed to provide real-time responses from concurrent users and applications. To be more specific, OLTP databases must provide real-time concurrent (multi-threaded) processing of all SQL transaction (writes/updates and reads). Another characteristic of an OLTP database, is the fact that its state (underlying data) is constantly changing. Examples of OLTP are databases that support e-commerce applications.
OLTP databases are highly Normalized relational databases. This means that there is very little or no data redundancy. This ensures data consistency (part of the ACID standard). Normalization is the process of arranging data into logical, organized groups of tables, reducing data repetition or going so far as to completely eliminating it. As a result the data is logically grouped into tables, and these tables form relationships with one another through the use of primary and foreign keys. There are different levels of normalization and OLTP data models usually meet the 3rd Normal Form also known as the Entity Attribute Relationship Model.

Tuesday, September 24, 2013

Interview Questions : DataWareHouse - Part 2


For more : Visit HERE




What is real time data-warehousing?

Data warehousing captures business activity data. Real-time data warehousing captures business activity data as it occurs. As soon as the business activity is complete and there is data about it, the completed activity data flows into the data warehouse and becomes available instantly.


What are conformed dimensions?
Conformed dimensions mean the exact same thing with every possible fact table to which they are joined. They are common to the cubes.


What is conformed fact?
Conformed dimensions are the dimensions which can be used across multiple Data Marts in combination with multiple facts tables accordingly.

Wednesday, August 14, 2013

Schema File in Datastage


Schema files and partial Schemas:

You can also specify the meta data for a stage in a plain text file known as a schema file. This is not stored in the Repository but you could, for example, keep it in a document management or source code control system, or publish it on an intranet site.

Thursday, August 08, 2013

Interview Questions : DataWareHouse - Part-1




What is Data Warehousing?
A data warehouse is the main repository of an organization’s historical data, its corporate memory. It contains the raw material for management’s decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. Data warehousing collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. It is a repository of integrated information, available for queries and analysis.

Wednesday, July 03, 2013

Teradata Users



 In Teradata, a user is the same as a database with one exception. A user is able to logon to the system and a database cannot. Therefore, to authenticate the user, a password must be established. The password is normally established at the same time that the CREATE USER statement is executed. 
The password can also be changed using a MODIFY USER command.

Monday, March 25, 2013

Difference Between The Continuous Funnel And Sort Funnel


# Continuous Funnel combines the records of the input data in no guaranteed order. It takes one record from each input link in turn. If data is not available on an input link, the stage skips to the next link rather than waiting.

# Sort Funnel combines the input records in the order defined by the value(s) of one or more key columns and the order of the output records is determined by these sorting keys.

Wednesday, October 03, 2012