In the current information age of rapid development, it is crucial for enterprises to master some big data analysis software and tools to support business decisions. What is the best business data analysis software for 2019? I’ll list some of the top data analytics software in the market.
FineBI is a new generation of self-service BI tools. It provides a wide range of services for enterprise customers. It provides big data analytics and data management solutions that can be helpful in promoting business growth. The FineBI platform assists with data visualization for explorative analysis and comes complete with enterprise-level management and control platforms to help users take action after their data analysis. With FineBI’s simple and smooth operation, strong big data performance, and self-service analysis experience, enterprises can fully understand and use their data so as to enhance the competitiveness of enterprises.
Tableau is one of the market leaders in big data visualization software. Tableau is particularly efficient in providing interactive data visualization for big data operations, deep learning algorithms, and various types of AI applications. It includes commonly used analysis charts and some data analysis models, which can quickly explore data analysis and make dynamic interaction diagrams.
This product has high stability and uses SQL to process data. Tableau’s technology is mainly divided into big data and visualization highlights. It covers BI and big data (mass data, real-time analysis), agile BI, self-service BI, exploratory BI, and is cost-effective. However, it does not support the program interface and instead implements via third-party outsourcing. Tableau BI is good in product capability, especially in big data performance, and can also support the extraction and analysis of hundreds of millions of data, while it has a mediocre performance in service.
Microsoft Power BI
Microsoft Power BI is a web-based business analysis tool suite that is good at data visualization. The main report connection process is on the client side, while the browser side can be simple report editing. Its connection to the data source requires a separate download of the MSI driver, rather than the current mainstream JDBC connection. The operations are mostly drag-and-drop, but its limited exploratory analysis capabilities make it unsuitable for custom development (which doesn’t meet our integration needs). Power BI boasts low learning cost and quick operation but has simple functions, which are unable to support complex business scenarios.
In its enterprise business intelligence application platform, users can have more intuitive and convenient access to information. It can satisfy users’ self-service requirements, including data query and report, OLAP, various business reports, dashboard, display on mobile terminal, and it has a unified service platform to support numerous management and maintenance functions.
This is a new generation of lightweight BI products that are being modeled, deployed, and used. It can only run on Windows system and C/S product architecture. It has advantages like using memory dynamic calculation, small amounts of data, and fast speed. When the data volume is large, the performance can be slow. However, at present, QlikView is mainly an agent, with poor localization and customization ability. Like Tableau, it has no big data processing ability, so it needs to dock with a data warehouse.
SAS is a leader in analytics and is for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. SAS is used for banking, finance, and medical statistics. SAS has a large number of published learning materials. This is the most widely used BI software and has been acquired by IBM. It has a strong database platform and is competent in the field of data management, data integration, and middleware expertise. It is difficult to learn SAS, but it is extremely valuable to master SAS.
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