Data warehouse is a database that was built to provide decision support that is separate from the operational database. Operational databases are databases used in the transaction process. So, then the data that in an operational or transactional database is separated into historical data that is used for analysis into a data warehouse.
Introduction to Data Warehouse
Data warehouse is the core of modern systems for decision making. Data in the warehouse can be used for information processing, analysis, and data mining. Because of this, the data warehouse is very useful to help a company to take steps in the right direction and to not make mistakes during the process.
The large amount of operational data and dimensions (the number of fields and records) is one reason data warehouses must be built. With large data, the query process to produce the required information will require a long time, and large dimensions can also affect the complexity of the queries made. Apart from this, the diversity of database sources is also one of the reasons for the construction of a data warehouse. The variety of sources will provide difficulties in obtaining information, because of differences in format, the process will also increase and make the time needed will be of a longer duration. Therefore, the data warehouse system must be built so that it is easy to get information and for quick decision making, because the data displayed must be fast and in real time.
Data warehouses have certain characteristics, being – subject oriented, integrated, time variant, and non-volatile. Managed data is data based on important subjects, for example customers, products, sales, and finance. Data models and analysis are focused on decision making rather than daily operations, so the view given will be simpler for certain subjects because unnecessary data will be discarded. Data collected consists of various sources, so cleaning and integration techniques are applied to maintain data integrity. The integration includes the consistency of names, attributes and conversions when moving data to the data warehouse.
Each structure in a data warehouse contains a time element, it is different from an operational database that does not necessarily contain a time element. The data time is longer when compared to the operational database in the form of current data, namely with a historical perspective of 5 to 10 years.
Data storage is separated from operational database because it will have an impact when accessing data. Both database systems must have a high performance. The operational database is designed for indexing, concurrency, and recovery. Whereas the data warehouse is designed for complex queries, multi-dimensional views, and consolidations. Then the data warehouse must be separated from the operational database because each must have a high-performance level on its own.
Data stored in a data warehouse does not require updating because the data does not require transactions, recovery, and concurrency. Then the data warehouse has only two operations namely initial loading and data access. Data update is not needed because before the data is entered into the warehouse, the data has passed through several stages so that the incoming data is valid, accurate, and has been converted. Because of the characteristics of the data warehouse, the data used in decision making will be very useful for a company and company can make informed and knowledgeable decisions.
Here are a few reasons as to why you should set up a data warehouse:
Helps better decision making
Company decision makers no longer must make important business decisions based on hunches and limited data. Data warehouses store credible facts and statistics, and decision makers will be able to retrieve information based on personal needs. In addition to helping make strategic decisions, data warehouses also have an important role in marketing segmentation, inventory management, financial management, and sales.
Quickly and easily access data
The next function of data warehouse for companies is to quickly and easily access data. Speed is an important factor that puts you above the competition. Business users can quickly access data from various sources, which means that the valuable time you have does not need to be wasted spent taking data from various sources. This function allows you to make quick and accurate decisions, with little or no support from your company’s IT department.
Data quality and consistency
Because the data warehouse collects information from different sources and converts it into a single and widely used format, your company’s departments will produce results that are consistent and consistent with each other. When data is standardized, your company could have confidence in its accuracy, and accurate data is important in making strong business decisions.
Provides historical intelligence
Data warehouses store large amounts of historical data so you can analyse different periods and time trends to make business predictions for the future. Data generated through these systems usually cannot be stored in transactional databases. In other words, it is used to produce reports from the transactional system. But, by using a data warehouse that has a historical intelligence function, you can use previous data to produce business alliances.
Produces high ROI
Return on investment (ROI) is the ratio between net income and investment costs resulting from the investment of several resources. High ROI means profitable investment returns. Data warehouse functions to provide a profitable investment return. This is because companies that have implemented it and the complementary BI system have generated more revenue. On the other hand, you can save more money than companies that have not yet invested in the system.
These are the advantages of having a data warehouse in place. Data warehouse is very important for any type of business you run. Especially if you want to profit from sound business decisions. Apply this sophisticated system to your business now to get several of the many benefits as listed above.
