Data wareHouse

Data wareHouse

What does Nonvolatile means? It means that if you once enter in a warehouse, the data should not be change. Logically because the main purpose of warehouse was to enable us to analyse what has happened or occured.

Time Variant

To be able to discover the main trends or known in business, the analyst will need a huge amount of a data. This is will going to be a different from online transaction processing, where its performance will requires a demand on historical data that will be move to an archive. The data warehouse will focus on the shift over time that will meant by the term called time variant

• Contrasting OLTP and Data Warehousing Environments
• Data warehousing and OLTP /contrasting

One of the biggest differences between those types of system is that the data warehouses were not usually in a 3rd normal form or 3NF data normalization that is common on OLTP environments

Warehouses and OLTP different kind of requirements

Examples will to be stated below:

I. A Workload

The data warehouses were also designed to accommodate the ad hoc queries. We might now be knowledgeable of the workload of a data on our data warehouses on advance, that is why a data warehouse must be optimized to do well for a huge variety of those that are going to be possible query operations.

predefined operations were only going to be a OLTP. The applications might be Specifically tuned or Develop to support only on these kind of operations.

II. The Data modifications

The data warehouse will going to be updated on its regular basis by ETL process, using a Bulk data modification style. The end users will not going to be directly updating the data warehouse .

The end users on a OLTP system routinely issued a data modification statements to its database. It should always be updated to its date, and should reflect to its current state of every business transaction.

III. Schema design

The data warehouses use denormalize or partially denormalized schemas on most of the time

Such a STAR CHEMA to be able to optimize its query performance

The system OLTP will use fully normalize schemas most of the time to be able to optimize updates, insertion or to delete performance, also to be sure of the data consistency

IV. The Typical operations

Particularly a data warehouse query will see on hundreds to millions of rows.

V. The Historical data 

(DW) commonly gather data by several months or years. The OLTP systems often stock its data from a few day, weeks or months. It will only stock belonging to the past data as wanted to be mostly fir the necessities of a current dealing

VI. Data Warehouse Architectures

The architectures will and data warehouses will only differ depends on its particular org circumstances.

The Data Warehouse Architecture (with a Staging Area)

Things that need to be know and process of the operational data before we put it to the warehouse. we can do it on a programmatically, thou most of the data warehouses is using a staging area i. the staging area will going to ease making summaries and also main warehouse management.

The Data Warehouse Architecture

We can customize our data architecture on different groups within our organization. We can simply add the data marts, which especially systems designed to a some line of the business

The (DW) or data warehouse was a system that will use for reporting its data analysis that were also considered as a main component of a business judgement. Dws were Main repositories of the integrated datas from certain or more disparate sources, it will store the current and also its historical data on a alone/single will be used for making an analytical reports.

Those data that will be stored in warehouse will going to be uploaded from the operational systems. Those data may pass onto operational data I might require the data cleansing, the access layers and also the data integration to house the key functions, while the staging layer will store a chafed data that extracted from every disparate sources. Integrations layers will combined the disparate data that are sets by changing the data from its staging layer most of time storing will change data on a operational data storing database. Also the combined data will going to be moved to a another database that most of the time known the data warehouse dbms, on that point the data will going to be arrange from its hierarchical groups, they called it dimensions, from facts and also from aggregated facts. A joined of facts and the dimensions are called commonly star schema. 

What will help us to recover the data? The access layer.

The major source of a data will be cleaned and change and will going to be available for the use of the managers and other professionals for data gathering,

the components of a data warehousing systems are the method to : 

• >recover
• >analyse data
• > to be extracted
• >change
• >load of the data

Researchers :

Clark Von Cabural
Jumar Satoridona
Jaymar Melitante
Gilbert Rovillos