Companies need to work with an increasing data flow to have a broader view of market trends and actions that need to be effective to promote continuous improvement. This scenario collaborates to increase the use of DataWarehouse in the corporate world.
This resource consists of an organization of databases for analysis of information and activities with a focus on Business Intelligence. DataWarehouse is considered a database that stores and organizes a large volume of information and makes it possible to create reports through histories.
We will present several details about the operation of this resource in this article. Which is increasingly adopted by corporations. Check out!
See how it works
DataWarehouse centralizes data obtained from various sources to facilitate access and consultation. The information is extracted in several formats (SQL, CSV, TXT, XLS etc.) through several resources, such as:
- CRMs;
- ERPs;
- Spreadsheets.
The data is usually sent to the Staging Area after being extracted a place for data quality and standardization processes. They are then forwarded to the Enterprise Data Warehouse (EDW) or Data Marts directly.
Thus, it is feasible to search the most relevant and updated information in a single place in an organized manner with a focus on ease of consultation. DataWharehouse has significant advantages for users. For example:
- Quick access;
- Low operating cost;
- Ease of use;
- Quality of information;
- Separation of operations according to the modality;
- Safety;
- Simplicity.
These factors show how this tool can be useful for an organization to manage data in a more strategic way which is very important for the decision making to be made within the best practices of the market.
Stay tuned for features
A DataWarehouse stands out for having several features that allow data analysis with a high level of accuracy. Let’s mention some striking aspects of this tool. Follow it!
Theme orientation
This characteristic covers the transactional systems adopted in a corporate application. For this reason, it is very relevant and guides all the modeling of the tool to prioritize the main themes of an organization.
In the case of a shoe store, the most sold products and the average ticket by customers can be worked on.
Integration
It is one of the most important features of this feature because it makes it possible to integrate the operational environment for DataWarehouse to function fully. In this way it is feasible to standardize information from several systems into a single representation. This allows data to be entered on a single basis.
Absence of volatility
It’s common for transactional systems to undergo several modifications, such as alteration, inclusion and removal of data. Data is filtered and cleaned to generate information before loading on the DataWarehouse platform.
After that they undergo only consultation and exclusion operations with no possibility of modifications. This contributes to this mechanism being characterized by non-volatility.
Variation with time
This item contemplates the maintenance of a history of information for a longer period when compared to other systems. This is possible because the data mining techniques aren’t adopted in real time.
Therefore there is no compromise in the performance of OLTP transactional banks. Data on the platform will always be linked to a certain period because it includes a time key that indicates the moment when the data was extracted.
Due to the designed environment DataWarehouse is able to gather several data from a single source. This action contributes a lot of the work of the analyst who also doesn’t need to be concerned with the redundancy of information a factor that facilitates decision making.
- Know the structure
A DataWarehouse is made up of several parts. Let’s point out the main segments of this platform. Look!
- Data sources
They consist of a corporation’s transactional systems and can be composed of various forms of data.
- Data Stage
It includes a storage location and includes a set of processes. It is responsible for extracting data from operating systems and cleaning. In addition it promotes the transformation, combination, duplication and preparation of data for the functioning of the DataWarehouse.
- Presentation server
It is the place where data is stored and organized for consultation by end users. In general this information is accessible in relational databases but it can also be stored by OLAP (OnLine Analytical Processing) technology since many Data Marts act only with data in the dimensional model.
- Data Mart
It is a logical subset of DataWarehouse. Its striking feature is to be divided by departments or segmentations necessary for the target audience.
- Data Mining
Its main assignment is data mining. It works with large masses of data that present several correlations with each other that aren’t easily perceived.
This mechanism allows an automatic scan to identify trends and patterns using pre-defined rules. This allows you to find data that would probably not be found in a normal search.
Data access tools
It’s necessary to pay attention to the format in which data are extracted and integrated into the processes of a DataWarehouse. Therefore it is important to know the activities involved in data transformation which are:
- Extraction: involves the removal of data from transactional systems and storage in the data stage;
- Load of processed dimensions: it consists of the feedback of the process in order to ensure that the data is represented correctly in a new format;
- Load, Replication and Recovery: the data is loaded into the corresponding data mart after being properly formatted. After that indexes are created or updated to increase the performance of consultations;
- Food: exposes the views of the data mart based on the priorities of users;
- Loading of model results: allows for possible changes to the data mart if it isn’t properly prepared for the applications chosen at the moment.
DataWarehouse presents models of architectures that vary according to the subject addressed. This is done to contemplate in an impeccable way to need of each company.
The choice of architectures (generic, two layers or three layers) must take into account the level of security and the complexity of the processes adopted in a company in relation to the use of data.
DataWharehouse is a platform that presents a different treatment in the use of data. For this reason companies are investing in this resource to access relevant information more easily and accurately which helps to improve decision making.