Data Modelling is Broadly classified into 2 types. a) E-R Diagrams (Entity - Relatioships). b) Dimensional Modelling.
Latest Answer : Dimension modelling means to define a datawarehouse architecture using any one of the availabale schemadimensionl modelling are 3 types 1. conceptual model 2. logical model3.physical modelconceptual model: gathering of all the requirementslogical ...
a)Star Schema - Simple & Much Faster. Denormalized form. b)Snowflake Schema - Complex with more Granularity. More normalized form.
Latest Answer : Is not star schema better performance wise (querying) as it has less no of join due to denormalized structure? Please clarify ...
Fact table - Table with Collection of Foreign Keys corresponding to the Primary Keys in Dimensional table. Consists of fields with numeric values. Dimension table - Table with Unique Primary Key. Load
Latest Answer : __________________ _______________ ________________|_________________| |______________ ...
Used for Look-ups. It is like a reference table. It is also used in-place of ODBC, OCI tables for better performance.
Latest Answer : We can also use the Hash File stage to avoid / remove dupilcate rowsby specifying the hash key on a particular fileld ...
What are other Performance tunings you have done in your last project to increase the performance of slowly running jobs?
Staged the data coming from ODBC/OCI/DB2UDB stages or any database on the server using Hash/Sequential files for optimum performance also for data recovery in case job aborts.Tuned the OCI stage for 'Array
First we execute the jobs that load the data into Dimension tables, then Fact tables, then load the Aggregator tables (if any).
Latest Answer : Simply by using "usage variyable" stage in job sequencers. ...
The above might rise another question: Why do we have to load the dimensional tables first, then fact tables:
As we load the dimensional tables the keys (primary) are generated and these keys (primary) are Foreign keys in Fact tables.
A. The jobs in which data is read directly from OCI stages are running extremely slow. I had to stage the data before sending to the transformer to make the jobs run faster.B. The job aborts
Scenario based Question ........... Suppose that 4 job control by the sequencer like (job 1, job 2, job 3, job 4 )if job 1 have 10,000 row ,after run the job only 5000 data has been loaded in target table remaining are not loaded and your job going to be aborted then.. How can short out the problem.
Suppose job sequencer synchronies or control 4 job but job 1 have problem, in this condition should go director and check it what type of problem showing either data type problem, warning massage, job
Latest Answer : Dear User. A datawarehouse is a repository(centralized as well as distributed) of Data, able to answer any adhoc,analytical,historical or complex queries.Metadata is data about data. Examples of metadata include data element descriptions, data ...