121⟩ Which technology should be used for interactive data querying across multiple dimensions for a decision making for a DW?
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“Data Warehousing Interview Questions and Answers will guide now that Data warehouse is a repository of an organizations electronically stored data. Data warehouses are especially designed to facilitate reporting and analysis about the data of any organization. So learn Data Warehousing concepts by Data Warehousing Interview Questions and Answers and get preparation of Data Warehousing Jobs Interview.”
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Informatica Architecture contains Repository, Repository server, Repository server administration console, sources, repository server and Data warehousing and it have the Designer, Work for manager, work for monitor combination of all these are called Informatica Architecture.
Data warehousing is the repository of integrated information data will be extracted from the heterogeneous sources. Data warehousing architecture contains the different; sources like oracle, flat files and ERP then after it have the staging area and Data warehousing, after that it has the different Data marts then it have the reports and it also have the ODS - Operation Data Store. This complete architecture is called the Data warehousing Architecture.
After the completion of reporting, reports will be sent to business analysts. They will analyze the data from different points of view so that they can make a proper business decisions.
The Developer created the mapping that can be tested independently by the developer individually.
For a faster process create aggregate tables and write better sql so that the process would fast.
Version dimension is the SCD type II in real time it using because of it will maintain the current data and full historical data.
We can link one universe to other universe in Universe parameters.
Drilling can be done in drill down, up, through, and across; scope is the overall view of the drill exercise.
If you want to run the graph through GDE then after save the graph just press F5 button of your keyboard, it will run automatically. If you want to run through the shell script then you have to fire the command at your UNIX box.
As the term suggests, a real-time data warehouse is a system, which reflects all changes to its sources in real time. As simple as it sounds, this is still an area of active research in the field. In traditional DWH, the operational system(s) are kept separate from the DWH for a good reason. The Operational systems are designed to accept inputs or changes to data regularly, hence have a good chance of being regularly queried. On the other hand, a DWH is supposed to do just the opposite - it is used to query data for reports only. No changes to data, through user actions is expected (or designed). The only inputs could come from the ETL feed at stipulated times. The ETL would source its data from the Operational systems just explained above.
To create a real-time DWH we would have to merge both systems (several ways are being explored), a concept that is against the reason of creating a DWH. Bigger challenges occur in terms of updating aggregated data in facts at real time, still maintaining the surrogate keys. Besides, we would need lightening fast hardware to try this.Near Real time DWH is a trade-off between the conventional design and the dream of all clients today. The frequency of ETL updates in higher in this case for e.g. once in 2 hours. We can also analyze and use selective refreshes at shorter time intervals, while complete refreshes may still be kept further apart. Selective refreshes would look at only those tables that get updated regularly.