Business intelligence (BI) and analysis platforms have long been an important part of business, but due to the rise of self-service BI tools, with the support of data scientists and database administrators, the responsibility of analysis has shifted from IT to business analysts.
As a result, BI has transformed from a recording system that generates monthly reports to interactively discover and share trends, forecasts, and answers to business questions based on data from various internal and external sources. Companies that use self-service BI can decide on a course of action within a few days instead of months.
1. Deployment and use
Tableau is a C/S architecture. It is necessary to install a desktop on the user terminal for analysis design, install the server on the server side, publish the module data and analysis on the server, and use the reader to view the analysis generated by the client, which can be disconnected on the web and mobile. View the analysis published on the server. The volume is large and the deployment is a little more complicated, and the client's cooperation is required for use.
Smartbi adopts B/S architecture, which is easy to deploy and upgrade. Let big data applications and analysis enter the work of employees and managers, inspire all levels of personnel to understand, mine and use data; promote the self-service analysis and data sharing of all employees, enhance the value of enterprise data assets, and promote business development and risk Control and internal management to promote digital transformation. It can also be integrated into projects developed by yourself.
2. Platform interface
Tableau separates the server from the client. Platform management and design are carried out separately. The product logic is clear, easy to understand, and user-friendly, but it is not conducive to IT department control and cooperation.
Smartbi puts the entire platform and design on one interface, and uses authority management to control the interface displayed by each user. Conducive to enterprise-level management and control.
3. Work flow
Smartbi is to configure the data for the administrator and create the corresponding business package. The business package contains the relevant data that the salesperson needs to use; the business is returned to the salesperson: no need to wait for IT staff, no need to mention processes, etc., 80% of the analysis needs It can be done by itself; and the IT technology department focuses on technology itself to reduce overtime, improve data management and metadata analysis, and focus on technological innovation. Decision makers can also quickly see the analysis.
Tableau's workflow is that analysts complete the entire process from data connection to new analysis, and decision makers directly view the analysis.
It can be seen from the above figure that tableau can only complete the function of data analysis. But Smartbi's self-service BI also includes ETL. Self-service ETL preprocesses business system data through simple drag-and-drop operations to solve the problems of scattered, messy, and inconsistent enterprise data. And tableau is just a pure analysis tool.
4. Data support and management
Smartbi supports Hadoop, Ms SQL Server, Oracle, DB2, Informix, Sybase, Teradata, MySQL, PostgreSQL, Greenplum, KingbaseES, Nanda General Gbase, Access, Excel, and various ODBC data sources; supports JDBC and JNDI connections Database, easy to configure and manage data source connection. In addition, other text-type heterogeneous data sources can also be supported through the JAVA data set function that comes with the product. Smartbi can connect to a certain database, then save it as an instance, and use it as a data source. Tableau supports fewer data sources, and it connects to the database and takes the table as the data source. The connection cannot be retained as the data source, which means that the data connection must be edited every time data analysis is performed, which makes the data table Adding becomes troublesome.