Shulou(Shulou.com)06/03 Report--

To put it simply, we can simply divide big data's analysis tool into two dimensions:

The first dimension: data storage layer-Datagram surface layer-data analysis layer-data presentation layer

The second dimension: user-department-enterprise-BI

1. Data storage layer

Data storage involves the concept of database and database language, it is not necessary to delve into this aspect, but at least understand the way of data storage, the basic structure of data and data types. SQL query language is essential, proficiency is the best. You can start with the basic structure and reading of commonly used select query, update modification, delete deletion, insert insertion and reading.

Access2003. Access07, etc., which is the most basic personal database, is often used for personal or partial basic data storage; MySQL database, which is necessary for departmental] level or Internet database applications, at this time, it is critical to master the database structure and the data query ability of SQL language.

SQL Server 2005 or higher, for small and medium-sized enterprises, some large enterprises can also use SQL Server database, in fact, in addition to data storage, but also includes data reports and data analysis, and even data mining tools are included.

DB2,Oracle databases are all large databases, mainly at the enterprise level, especially for large enterprises or for mass data storage. In general, large database companies provide very good data integration application platforms.

BI level, in fact, this is not a database, but a data warehouse for enterprise applications based on the previous database. DataWarehouse, data storage based on DW level is basically a business intelligence platform, integrating a variety of data analysis, reporting, analysis and presentation! BI-level data warehouse combined with BI products is also a major trend in recent years.

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2. Newspaper surface layer

Enterprises store data that need to be read and displayed. Report tools are the most commonly used tools, especially in China. The traditional report solves the problem of presentation. At present, the domestic soft report FineReport is considered to be the top in the industry, which is a report with the idea of data analysis. Because of its excellent interface opening function, filling in the report, and form function, it can get in and out of the data, covering the functions of early business intelligence.

Tableau, like FineBI, can be divided into data presentation layer as well as newspaper surface layer. FineBI and Tableau are both excellent software in recent years, which can be used as visual data analysis software. I often use FineBI for reporting and visual analysis from the database. Relatively speaking, visual Tableau is better, but FineBI has another identity-business intelligence, so it is better at big data's processing ability.

3. Data analysis layer

In fact, there are many analysis tools in this layer. Of course, the one we use most is Excel, and I often use statistical analysis and data mining tools.

Excel software, the higher the first version, the easier to use this is for sure; of course, for Excel, many people just master the 5%Excel function, Excel function is very powerful, and even complete all the statistical analysis work! But I often say that if you have the ability to turn Excel into a statistical tool, it is better to learn statistical software.

SPSS software: the current version is 18, and the name has been changed to PASW Statistics. I started programming analysis in Dos environment from 3.0. the changes of the current version can also see the changes of SPSS social science statistics software package. From attaching importance to medicine, chemistry, etc., we have paid more and more attention to commercial analysis, and now it has become a predictive analysis software.

SAS software: SAS is actually more powerful than SPSS, SAS is a platform, EM mining module platform integration, relatively speaking, SAS is more difficult to learn, but if you master the SAS will be more valuable, such as discrete selection model, sampling problems, orthogonal experimental design or SAS is better to use, in addition, SAS learning materials are more, but also open, there will be gains!

JMP Analysis: an Analytical Branch of SAS

XLstat: a plug-in for Excel that can perform most of the SPSS statistical analysis functions

4. Presentation layer

The presentation layer is also called data visualization, and each of the above tools provides almost a little presentation function. The visualization capabilities of FineBI and Tableau have been mentioned above. In fact, the visualization of Excel is getting better and better in recent years. With some plug-ins, it feels better to use it.

PPT: commonly used in the office to write data analysis reports

Xmind& Baidu brain map: sort out the process, help thinking and analysis, and show the level of data analysis

Xcelsius software: Dashboard production and data visualization report tools, you can directly read the database, modeling in Excel, Internet display, the most important feature can be achieved in PPT dynamic reports.

Finally, it should be noted that this classification is not to distinguish between the software, just to illustrate the application of the software. Sometimes we use the database for report analysis, sometimes the report is the analysis, sometimes the analysis is the display; of course, sometimes the display is the analysis, the analysis is also the report, the report is the data storage!

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