What is the Datawarehouse

A datawarehouse is a collection of data in which the company's information is integrated and that is used as support for the managerial decision-making process. Although various organizations and individuals come to understand the approach of a Warehouse , experience has shown that there are many potential pitfalls.

Gathering the appropriate data elements from various application sources in a centralized comprehensive environment, simplifies the problem of access to information and, consequently, accelerates the process of analysis, consultations and the shortest time of use of the information.

The applications for decision support based on one data warehousing can make more practical and easy data mining for greater efficiency of the business, which is not achieved when using only the data from operational applications (which help in operation of the company in its daily operations), in which the information is obtained by carrying out independent and often complex processes.

A data warehouse is created by extracting data from one or more operational application databases . The extracted data is transformed to eliminate inconsistencies and summarize if necessary and then uploaded to the data warehouse.

The process of transforming , creating the variant time detail, summarizing and combining the data extracts, help to create the environment for access to Institutional information. This new approach helps individuals, at all levels of the company, to make their decision-making more responsibly.

The innovation of Information Technology within a data warehousing environment can enable any organization to make optimal use of data as a key ingredient for making process more effective decisions. Organizations have to take advantage of their information resources to create the information of the business operation, but the technological strategies necessary for the implementation of a complete datawarehouse architecture must be considered.

The most important characteristics of this data repository are the following:

1.            Theme oriented . The data in the database is organized so that all data elements relating to the same event or object in the real world are linked together.

2.            Variant in time . The changes produced in the data over time are recorded so that the reports that can be generated reflect these variations.

3.            Not volatile . The information is not modified or eliminated, once a piece of data is stored, it becomes read-only information, and is kept for future consultations.

4.            Integrated . The database contains the data of all the operational systems of the organization, and such data must be consistent.

A Datawarehouse is structured as follows:

1.            OLAP Datamart : They are based on the popular OLAP cubes, which are built by adding, according to the requirements of each area or department, the dimensions and necessary measures of each relational cube. The way of creating, operating and maintaining OLAP cubes is very heterogeneous, depending on the final tool used.

2.            Datamart OLTP : They can be based on a simple extract from the datawarehouse, however, the common thing is to introduce improvements in its performance (aggregations and filtered are usually the most common operations) taking advantage of the particular characteristics of each area of the company. The most common structures in this sense are report tables, which come to be reduced feasible tables (which add the appropriate dimensions), and materialized views, which are built with the same structure as the previous ones, but with the aim of exploiting the rewriting of queries (although it is only possible in some advanced DBMS, such as Oracle).

A Datamart is a departmental database, specialized in storing data for a specific business area. It is characterized by having the optimal data structure to analyze the information in detail from all the perspectives that affect the processes of said department. A cube can be fed from the data of a data warehouse, or integrate by yourself a compendium of different sources of information. Therefore, to create the datamart of a functional area of the company, it is necessary to find the optimal structure for the analysis of its information, a structure that can be mounted on an OLTP database, such as the datawarehouse itself, or on a database OLAP. The designation of one or the other will depend on the data, requirements and specific characteristics of each department.

Datamarts that are equipped with these optimal analysis structures have the following advantages:

1.            Little data volume

2.            Faster consultation

3.            Simple SQL and / or MDX queries

4.            Direct validation of information

5.            Ease of data historicization


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