It is one place for SQL,ORACLE, datawarehouse and testing concepts
29 May 2016
28 February 2016
DWH: What is Data warehouse ?
What is Data warehouse ?
A Data warehouse is a repositary which stores integrated information for querying and analysis purpose. It has data collected from multiple heterogeneous source system.
According to Bill Inmon who is also known as" Father of Data warehouse", Data warehouse should be :
What is Data warehouse ?
A Data warehouse is a repositary which stores integrated information for querying and analysis purpose. It has data collected from multiple heterogeneous source system.
According to Bill Inmon who is also known as" Father of Data warehouse", Data warehouse should be :
- Subject Oriented : It helps in synthesizing data as per the subjects.
- Time Variant : It stores data over a period of time.
- Integrated : It integrates data from multiple source system.
- Non Volatile : Data in Data warehouse is never deleted.
27 January 2016
DWH: OLTP Vs OLAP
DWH: OLTP Vs OLAP
OLTP(Online Transactional Processing) OLAP(Online Analytical Processing)
1.It deals with Transactional / Operational Data 1.It deals with Historical Data
2.Databases are normalised to facilitate frequent 2.Databases are de-normalised to facilitate insertion,updation and deletion queries and analysis
3.Old data is purged or archived 3.Old Data or Historical data is stored to do trend analysis and future predictions.
4.Queries are small and it deals with small 4.Queries are complex and it deals with amount of data huge amount of data
Eg: Updation of Account Balance Eg: Total sales in North India
5.Updates happens frequently 5.Updates does not happen frequently.
6.Response time is very fast. 6.Response time is slow
7.Number of Joins are more as Table is 7. Mostly less number of joins as Table is in Normailesd. de-normalised.
OLTP(Online Transactional Processing) OLAP(Online Analytical Processing)
1.It deals with Transactional / Operational Data 1.It deals with Historical Data
2.Databases are normalised to facilitate frequent 2.Databases are de-normalised to facilitate insertion,updation and deletion queries and analysis
3.Old data is purged or archived 3.Old Data or Historical data is stored to do trend analysis and future predictions.
4.Queries are small and it deals with small 4.Queries are complex and it deals with amount of data huge amount of data
Eg: Updation of Account Balance Eg: Total sales in North India
5.Updates happens frequently 5.Updates does not happen frequently.
6.Response time is very fast. 6.Response time is slow
7.Number of Joins are more as Table is 7. Mostly less number of joins as Table is in Normailesd. de-normalised.
10 January 2016
SQL - DELETE and TRUNCATE
SQL- DELETE and TRUNCATE
Major difference between DELETE and TRUNCATE are as follows:
DELETE TRUNCATE
1. DELETE is DML Command 1. TRUNCATE is DDL Command
2. WHERE clause can be used 2. WHERE clause cannot be used
along with DELETE. along with TRUNCATE
3. It removes data from the table 3. It removes all data from the table
based on WHERE clause.
4. It puts lock on a row . 4. It puts locks on a table
5. It is slower as it keeps log. 5. It is faster as it does not keep log.
6. Space is not released. 6. Space is released.
7.Syntax: 7.Syntax:
DELETE FROM table_name TRUNCATE TABLE table_name
[WHERE condition]
Major difference between DELETE and TRUNCATE are as follows:
DELETE TRUNCATE
1. DELETE is DML Command 1. TRUNCATE is DDL Command
2. WHERE clause can be used 2. WHERE clause cannot be used
along with DELETE. along with TRUNCATE
3. It removes data from the table 3. It removes all data from the table
based on WHERE clause.
4. It puts lock on a row . 4. It puts locks on a table
5. It is slower as it keeps log. 5. It is faster as it does not keep log.
6. Space is not released. 6. Space is released.
7.Syntax: 7.Syntax:
DELETE FROM table_name TRUNCATE TABLE table_name
[WHERE condition]
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