Does the hottest enterprise really need Bi

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Does the enterprise really need Bi

does the enterprise really need Bi

this is a thought-provoking question. Bi may be too profound for many people. It's easy to understand from another angle: does your company need data analysis? Financial analysis, cost analysis or market analysis? Does your company need good analysis tools to speed up the analysis? If the above two answers are yes, your enterprise needs Bi

there should be no water or acid in the oil. Simply put, Bi (Business Intelligence) is an analysis tool. In the early era of information technology, analysts spent a lot of computing time with pen and paper (at most, there is a calculator), so that it is possible to analyze data from a perspective. Later, with the development of digitalization and the emergence of louts, Excel and other tools, the collation and analysis of data are more convenient. At this time, on the one hand, based on the help of the above tools, on the other hand, based on market demand, the amount of data that enterprises need to analyze is becoming larger and larger

however, because these analysis tools are not convenient for multi-dimensional data analysis, coupled with the sharp increase in the amount of data to be analyzed, many enterprises hope to carry out multi-dimensional data analysis directly and in real time from the database in which the enterprise operates. The place where a large amount of data and data are stored is called data warehouse (DW), and the whole part of multi-dimensional data analysis is called 3 Jinan assay low temperature tank features: Business Intelligence (BI)

the question now is, can we complete the dream of enterprise Bi by spending a lot of money and buying good Bi tools? As far as I know, some enterprises have spent a lot of money on good Bi tools, but the tools they bought are really popular. In the end, 90% of the employees in the enterprise still use Excel for data analysis. The reasons for the poor performance of Bi can be classified as the following:

1 This is the most commonly seen but often the most important problem. As mentioned earlier, business intelligence (BI) must be based on data warehouse (DW), so there are only good Bi tools, but the data warehouse at the bottom can't provide real-time and stable services according to the requirements of the Bi tools at the top. It's like building a house. It's obviously that the stratum is not stable, But it is impossible to build the building high and beautiful. In this case, the best tool is not easy

2. Lack of professional data analysts: no matter how "intelligent" the computer is, or not as smart as the human brain, it is just "faster" than the human brain. Bi tools only facilitate and accelerate the analysis of data, but the direction of data analysis and the choice of effective and relevant data still need to be decided by the human brain. In other words, a person who is familiar with the content and architecture of data and has business sensitivity is still required to participate in the import and operation of the whole Bi solution. However, the reality is that most enterprises have high expectations for the Bi tool itself. On the contrary, in the process of introduction, they do not timely let the talents in this field play their talents and be familiar with the use of Bi. In the end, Bi staff were forced to do their own database analysis, and these people continued to use their excel

3. The data has not been properly converted: most of the data in the data warehouse is transferred from the database in the internal system of the enterprise. Therefore, these data are not in terms of output, but in terms of the definition of data structure or the data itself, which are originally read and stored by the system program. For example, in the structure of RDBMS, we use the correspondence between PK and FK as the relationship between the two data tables. Some system developers have a good habit of standardizing these in the database, while others do not. However, no matter what, we still use the syntax of the database to make a definition. Most of the ordinary data analysts cannot understand such a definition. Data analysts do not necessarily understand such data, so appropriate conversion is required for these data to facilitate the use of data analysts

4. Lack of maintenance of database system personnel: many enterprises will misunderstand that buying Bi tools and installing them can operate smoothly. But he didn't expect that on the one hand, the data in the data warehouse will continue to grow with the growth of time. On the other hand, the data in the data warehouse will also need to be adjusted with the change of analysis requirements and the change of enterprise type. Therefore, if there is no database system personnel to maintain the data in the data warehouse at any time due to the needs of the enterprise, the data architecture in the data warehouse will be in a mess over time, In this case, there is no way to provide good efficiency. Therefore, in this case, as the data grows, the efficiency of each analysis result becomes worse and worse. The first report takes one hour to produce, but later it takes ten hours. Of course, slowly, such a tool is increasingly not accepted by analysts

5. Lack of good presentation: how should the report produced after BI data analysis be presented to the boss? Is the presentation real-time enough? If the boss doesn't like this presentation, or the boss must wait a long time to get such data. At this point, no matter how much data analysis you do, you won't get the favor of the boss. In that case, over time, no one wants to use this tool again

to sum up, Bi should not only be regarded as a "tool", but should be viewed from the perspective of solutions. If there is no perfect overall supporting plan, no matter how good the Bi tool is, it may eventually become a waste. Interestingly, the better the tools, the better the supporting planning required by the market rules. On the contrary, the less sophisticated tools do not need too much supporting planning. This should be one of the reasons why excel is still the mainstream tool for Bi analysis. (end)

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