Interpretation of business intelligence 2-components of business intelligence

Interpretation of business intelligence 2-components of business intelligence

Once we know what business intelligence (Business Intelligence) is, let's take a look at what business intelligence/business intelligence includes and what tools/technologies are needed to build a business intelligence system.

Generally, business intelligence includes the following parts (the Division methods may vary in different systems, but they are essentially the same ).

* ETL: Extract, convert, and load data. That is, to convert the data in different forms and distributed in different places into a well-organized and unified place for data storage (data warehouse ).

ETL can be implemented through specialized tools, or through any programming or similar technology.

* Data Warehouse: a standard definition is that a data warehouse is a collection of theme-oriented, integrated, time-varying, and non-loss-prone data. It is a decision-making process that supports management departments. For details, see http://www.ithao123.com/datawarehouse/0003.html.

Simply put, a data warehouse is the place where data is stored. It may be either an original business database or a separate generation. It may be a standard relational database or a special product with specific analysis features.

* Query: Find the required data. Due to the differences in demand diversity and complexity, the query may be the simplest way to find "All people surnamed Zhang" from a table ", to search for and generate complex results based on complex conditions and complex relationships.

* Report Analysis: view results and analyze data in a predefined or customized manner. Displays manually or automatically queried data in the desired form (including computing and comparison, various presentation formats, and various charts) to users, it allows users to drill down the data layer by layer, and flexibly perform new analysis and view the results according to various requirements.

In this field, reports have evolved from fixed reports in a narrow sense to flexible business requirements.Production at any timeVarious reports, various analysis and data research processes.

* OLAP analysis: Multidimensional Data Analysis analyzes data in multiple dimensions at the same time. To understand OLAP analysis, the simplest example is the pivot table in Excel.

It should be pointed out that OLAP can be divided into broad and narrow terms. The broad OLAP is relative to OLTP, which can be said to include query, report analysis, OLAP analysis and data mining, but what we really talk about is the narrow sense of OLAP, that is, multi-dimensional data analysis.

OLAP analysis is generally implemented by modeling and creating cubes, however, there are also some simple OLAP tools that can be used to analyze small data volumes and low complexity without modeling (an Excel PivotTable is an example ).

* Data Mining: A process of searching for information you are interested in or have valuable information in large databases. Compared with the previous sections, data mining is the most uncertain. If you understand the difference between it and the query, it seems that if the data is easy to be found, it is the query. If it is very difficult to find out, it is mining.

These parts are not essential to each part, but must be analyzed based on the actual situation of the application. Generally,Data Warehouse(In a broad sense, a considerable portion of the cases refer to Standard relational databases) andQuery,Report AnalysisIt is essential, while other functions may vary depending on the needs of applications.

In addition to the substantive and technical components mentioned above, there are also many application-layer concepts related to business intelligence, such as Enterprise Performance Management and dashboard) warning and decision support. These concepts are of great significance in application and some related auxiliary technologies, but they are basically based on the above components.

From the above explanation, we can see that business intelligence is neither mysterious nor simple.

It is not mysterious. It means that, even if you simply take a database, you can make several views or use stored procedures to convert the data and write a program so that users can query the data, write some programs or use a free report tool to prepare reports. Using Excel for OLAP analysis can also be called a business intelligence application.

However, with the increase of data volume and complexity and the enhancement of user functions, each of the above functions may be very complex and can be achieved through products with powerful functions in various fields.

Another point worth noting is that there is a big difference with ERP. The independence between the components of business intelligence is very strong, because the data in it is standardized. You can use Informatica for ETL, Oracle for data warehousing, andRunqianPerform query and report analysis, and use Cognos for OLAP analysis to achieve better results in various fields.

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