In terms of technological advancements, the Data Warehouse is critical because of its connections to the BI (Corporate Intelligence) domain, which provides help to business management.
With her arrival, as well as other instruments like:
We can now make decisions based on data analysis so that we can be directed in an insightful and secure way, thanks to tools like Data Analyst, Data Loss Prevention, Big Data, and Data Lake, among others.
We all know that with today’s technological advancements, it’s critical that there are no faults in these areas; as a result, data collecting, monitoring, and analysis security has become a hot topic in a variety of social and market sectors.
What is data warehouse?
The term “data warehouse” refers to the storing of data, and it was first investigated in 1980. This phrase began as an intellectual idea that became better understood and dissipated over time.
People came to grasp that it was vital to design tools that would help in certain industries, such as data security and transactional systems, as technology and the use of new tools progressed.
As the needs grew, so did the demand for data; when it used to be able to put everything in folders, that is no longer the case! These new tools are required by volume, security, and speed!
But what exactly is a Data Warehouse? It is a sort of data management system that uses machine learning techniques to facilitate and support BI (Business Intelligence) activities.
In addition to being derived from a wide range of application and application transaction log files, it enables advanced analysis and frequently contains enormous volumes of historical data.
How does it work?
Because the Data Warehouse functions as a kind of central warehouse, your data can come from a variety of sources, including one or more data sources.
After being processed, translated, and loaded, information from a transactional data system and other relational databases can be accessed by users.
It is possible to generate numerous actions with this data by accessing it, such as using BI tools, SQL Developer, and spreadsheets. The ETL is used in the data removal process (Extract Transform Load).
But what is ETL (Extract Transform Load) and how does it work?
ETL (Extract Transform Load) is a process that consists of a few steps:
Data is extracted from numerous application sources and then processed in this step, which might be comprehensive or incremental.
Full: it’s impossible to tell whether or not the info has changed!
Some source systems can detect changes made between unstructured and structured data in an incremental manner.
Transformation: Some rules are established to transform the retrieved data according to the requirements, such as integrating data from two different sources.
It’s also a component of item aggregation, linkage, and categorization!
Loading: This is the final step, and it consists of transforming the loaded data into the data warehouse for further analysis.
Types of Data Warehouse
There are numerous types of data warehouses available nowadays, which might differ depending on requirements and specifications! However, the following are the most frequently encountered:
Enterprise Data Warehouse: A central warehouse that serves the entire firm and organises and represents data in a consistent manner; access is restricted.
Operational Files: also known as ODS (Operational Data Store), it is used in conjunction with operational data when OLTP fails, it is updated in real time, and it is widely utilised for everyday operations.
Data Marts are a subset of Data Warehouses that are utilised in a specific line of business, such as finance. They are self-contained, meaning the data comes straight from the sources.
Benefits of Data Warehousing
Companies that adopt this tool have a capacity to store and collect data with greater security, ease, precision and efficiency, in addition to this, there are some factors such as:
- Data quality: data is arranged in a qualified manner so that when requested, it is available for your analysis;
- Fast access: it is a system that allows easy and quick access, as they are displayed in real-time;
- Source diversity: As it is a central system, data can come from one or more sources;
- Number of files: you have the permission to archive a large number of data, in a safe and organized way, being able to request them whenever you want;
- Decision making: one of the reasons that made data warehousing widely used is in relation to decision making, because with the data you can maximize it in this sense, for a safe and effective path.
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