Tableau is not necessarily the best, domestic bi can also break the siege!

Now, Baidu is a business intelligence or BI tool, always see tableau figure. Not that Tableau's marketing is doing well, but that the perception and choice of business intelligence tools at home seems to fall on tableau. Cause regardless of industry outside the concept of business intelligence has a biased view, think is a front-end display tool, is a chart.

This is not a denial of tableau. Indeed, Tableau's visualization and charting capabilities are well appreciated by the domestic BI vendors. But from the perspective of business intelligence, the focus of business on BI is more about the performance of data processing (volume, speed, stability), product suitability (development, integration), and analysis efficiency (presentation effect, operational experience). As a result, the development of BI has a lot of space.

So, back to the question, how should domestic bi tools break through?

Let's talk about business intelligence first. Business Intelligence was originally defined as the use of modern data warehousing technology, online analytical processing technology, data mining and data presentation techniques for data analysis to achieve business value. As a tool, business intelligence is used to process the existing data in the enterprise and transform it into knowledge, analysis and conclusions, assist the business or decision makers to make the right and wise decisions, help the enterprise to better use the data to improve the quality of decision-making technology, including from the Data Warehouse to the analysis system. So business intelligence is strictly a solution, based on the enterprise's existing IT technology architecture, to provide fast and accurate data analysis solutions.

From more than 10 years of sail soft company in the field of enterprise data analysis, combined with Finebi's product positioning, we can sniff out such a few:

1, for the enterprise data analysis needs to stick to the atmosphere

Each enterprise's it construction is different, the database is diverse, the data is normative, the development and integration of the system needs are not the same. In addition to supporting various types of databases and data sources, BI also supports Hadoop, Greenplumn-class big data platforms, and various data warehouses. For some enterprises have data warehouse, and some enterprises have simple database, some enterprise data volume, some enterprise data General difference demand, BI tools can provide different solutions for different hardware and software facilities of the enterprise. This, Finebi can give two ways to access the Enterprise Big Data Volume: Finedirect (direct Connect) and Fineindex (built cube). The Fineindex can be used to extract data, update data incrementally, and realize fast data analysis. Finedirect provides a SQL-based direct-connect engine that supports 1 billion to billions of data access and real-time data analytics for big data platforms.

2. data analysis is not limited to presentation, but more to exploration

Explore here can be understood as two aspects, first, the front-end data display has "exploratory guidance", how to understand? The present data show is based on the historical data of the induction and reorganization, lack of guidance for decision-making. The leader to get the report, understand that the sales of a certain area rise, decline, a period of product market heat is low, these conditions can be said after reading even, the leader still do not know what to do, he wants to see compared with previous years, the report has to pass again. This requires a very strong interaction between the charts, and the user can view them in a deep, multi-angle way. such as Finebi data drilling, data slicing and data rotation and other multidimensional analysis operations, as well as the spa spiral aggregation analysis can be done for the front-end data simple processing. The second is "in-depth analysis". The current business intelligence bi lacks the function of data mining, the development of BI tools can be more inclined to data mining and predictive analysis, such as integration with R language, including classification prediction, cluster Analysis, association rules, time series pattern and so on.

3. Keep the "lightweight" attribute

The current use of BI is gradually biased towards business analysts, tools need to be lightweight, reduce technical problems. Domestic BI tools for the localization of enterprise needs should have more advantages, the user analysis habits and business logic has a more accurate understanding, so this advantage should be maintained and in-depth development.

Therefore, in the current domestic market, BI development is still in the slow heat stage, the future, should be unlimited potential.

Tableau is not the best, and domestic bi can break the siege!