Industry Revolution brought about by agile Business Intelligence

The overwhelming introduction of big data makes everyone dazzled. Although the information is wonderful, we also see the value behind big data, but many enterprises do not know how to start.

With a pragmatic attitude and low cost, Alibaba Cloud quickly captures and analyzes big data in real time to obtain key information required for core business and strategic decision-making, thus, improving the level of business management and strategic decision-making, and ultimately creating great commercial value may be the best interpretation of the value of big data.

In the process of analyzing big data, the traditional data mining/Business Intelligence approach is that it personnel build models based on the analysis needs in advance, and create secondary tables or cubes, summarize the data in advance, and the business staff can view the analysis result report at the front end.

This practice has been mature for many years, but there are also some problems:

1. the reports viewed by business personnel are relatively static. The calculation methods of dimensions and measurements for analysis have been preset During modeling and cannot be changed. For example, if the calculation method is set to sum or average, to change the variance, you must go back and modify the model;

2. When the analysis requirement changes, the business personnel cannot directly adjust the report. It personnel need to re-model or modify the existing analysis model, which takes a long time and has a long response speed.

The underlying cause of these problems is that the past technical architecture lacks the computing capability for massive data and requires data calculation and summarization through modeling, secondary tables, and cubes.

Solution-agile Business Intelligence

With the development and evolution of technology, the Business Intelligence field has ushered in a new generation of agile Business Intelligence innovation. Data analysis using agile Business Intelligence has the following advantages:

Analysis reports cannot be viewed only. Data presentation is the starting point rather than the ending point. When you see the data, you must be able to perform interactive analysis, perform in-depth mining, discover problems, find answers, and take actions. The process of interaction with data must be fast enough. If you wait three or five minutes for the result to be displayed each time you click, interaction analysis cannot be performed. Based on the big data processing technology, agile business intelligence can respond to TB-PB-level data in seconds;

The analysis report should allow non-IT Department colleagues to make it directly on the analysis platform. You cannot submit all the analysis report requirements to the IT department, which seriously increases the burden on the IT department. Agile business intelligence is easy to implement and operate, and can be directly used by business personnel;

Analysis reports often require changes at the data layer. It departments need to improve the data layer and business layer. The traditional business intelligence platform needs a month or two to sort out models and design Meta, DWD, and DWA, ETL and cube. Agile Business Intelligence does not require prior modeling. It allows you to flexibly adjust the analysis dimensions and report presentation during the analysis process. demand changes can be responded within one day, improving your insight and decision-making capabilities.

Principles of agile Business Intelligence

Unlike the weight modeling and unified view of traditional business intelligence, agile business intelligence uses lightweight modeling and N views. Without creating two tables and cubes, data can be directly analyzed when connected, in addition, the business staff can adjust the calculation methods of dimensions and measurements in real time, greatly increasing flexibility and truly achieving data conversation.

650) This. width = 650; "src =" http://s7.sinaimg.cn/large/003cZYBezy6KaUPw8pE06 "style =" border: 0px; margin: 5px auto 0px; padding: 0px 0px 5px; "alt =" 003czybezy6kaupw8pe06 "/>

I think you may have a question: In this convenient way, why does traditional business intelligence not adopt this architecture? As mentioned above, the traditional technical architecture has not introduced the current big data technology. In the face of massive data, the results cannot be displayed within a few seconds after a user clicks, therefore, data must be summarized in advance through modeling to ensure the speed at which analysis reports are presented. The premise for achieving agile business intelligence is that the performance of data processing using the new architecture has been improved dozens of times, involving technologies such as distributed computing, memory computing, column storage, and in-database computing.

650) This. width = 650; "src =" http://s4.sinaimg.cn/large/003cZYBezy6KaURhUbN03 "style =" border: 0px; margin: 5px auto 0px; padding: 0px 0px 5px; "alt =" 003czybezy6kaurhubn03 "/>

Therefore, agile business intelligence allows enterprises to quickly gain insight into the meaning and value of data through lower costs and shorter launch cycles.

650) This. width = 650; "src =" http://s2.sinaimg.cn/large/003cZYBezy6KaUROtJDc1 "style =" border: 0px; margin: 5px auto 0px; padding: 0px 0px 5px; "alt =" 003czybezy6k1_tjdc1 "/>

Industry Revolution brought about by agile Business Intelligence

"Free Man" mentioned a saying that SF Express Wang Wei said-sometimes, just fast, can change an industry.

650) This. width = 650; "src =" http://s9.sinaimg.cn/large/003cZYBezy6KaUU6bsAe8 "style =" border: 0px; margin: 5px auto 0px; padding: 0px 0px 5px; "alt =" 003czybezy6kauu6bsae8 "/>

Let's look at a real case.

An Internet media/Research Institute faces the following problems:

The Agency is the largest Internet media/research institution in China. More than 70% of overseas listed companies reference its research and analysis report. At the same time, it provides customers with customized consulting report services, which can be divided into offline reports and software services;

The customer's customized requirements are changeable. If a report is generated, the delivery cycle should be three to four weeks, and if the software is provided, the delivery cycle should be six months. Because of the high labor cost and long iteration cycle, you cannot undertake projects that require too many reports. You can only create a few customized projects each year;

Therefore, the organization hopes to use business intelligence tools to improve business efficiency and income space.

Summarize the requirements of this institution:

Example of project requirements: Based on the time dimension, website summary, the user's source region, origin domain name, page access times, and stay time, statistics on the number of valid visits, bounce rate, visitors, new visitors, number of visits, number of days of return visits, and other related data. It is necessary to dynamically add conditions and analyze the data obtained from user behavior monitoring to gain a more detailed and clear understanding of user behavior habits;

Tens of millions of data records per day, and different website customers have different analysis needs. The flexible and changing multidimensional analysis requirements pose a higher challenge to the analysis performance, traditional databases and hadoop architectures cannot meet high-performance real-time analysis needs;

Foreign products, such as IBM, sap, and Oracle, are expensive and affordable for millions of users;

Most of the domestic products are the previous generation of business intelligence, which requires prior modeling and analysis. It is difficult to cope with flexible multi-dimensional analysis and change requirements, and the processing capability for large data volumes cannot meet the requirements.

In the end, the organization adopted agile Business Intelligence Technology to import detailed data (about 5 billion pieces) from three months to yonghong technology's agile business intelligence system, and directly customize the analysis and presentation of reports. This action brings huge benefits to customers:

Improved business efficiency: After using agile business intelligence tools, compared with the original analysis methods based on Excel and SQL programming, the offline report delivery cycle is shortened from 3-4 weeks to less than 1 week, software Delivery is shortened from half a year to one month;

Increase in project sources: projects that were not yet fully determined in their original demands were unable to be delivered due to fear of changes in requirements. After using agile business intelligence tools, you can quickly build a prototype within a few days to demonstrate to customers. Any demand changes can be adjusted within one week. Through this fast prototype trial and error method, you have the ability to undertake such projects;

Larger income space: as business efficiency is greatly improved, more projects can be undertaken, and the revenue space has increased several times;

Customer Satisfaction improvement: this service can quickly respond to customer needs and changes, and greatly improve customer satisfaction and retention rate.

Moreover, the institution has also undergone an innovative model transformation:

Based on Agile business intelligence tools, the organization has built a new SaaS platform to further improve user experience and provide customers with intuitive and interactive analysis reports.

Through the SAAs account sales model, stable long-term sustainable revenue has changed the revenue model originally based on independent projects.

The Organization's value description has changed from a media/consulting service company to an Internet application provider that provides big data services, significantly increasing the value of the Capital Market

Its subsidiaries quickly followed up on the use of agile business intelligence tools and changes in New Models

This is a case of a single enterprise. In fact, agile Business Intelligence has a great impact on individuals, enterprises, and even the industry.

Personal changes:

Business personnel can perform interactive exploration with data through self-service, perform data analysis more quickly, and gain insight into the meaning and value of data.

IT staff are no longer dragged down on other high-value jobs by heavy modeling modification tasks, and productivity is released.

Changes to enterprises:

For enterprises with big data, such as consulting research institutions, internet marketing agencies, public opinion/business analysis agencies, precision marketing agencies, and traditional enterprises in various industries, whether internal use data, or to provide external data services, there are more agile and efficient methods.

For enterprises or departments with small data, you do not need to use complex system tools for data mining when conducting market analysis, financial analysis, sales analysis, and customer analysis. The threshold for analysis is greatly reduced, this means that the majority of small and medium-sized enterprises that have been rejected by business intelligence vendors due to the threshold of cost, implementation cycle, and complexity can truly start the data mining journey through agile business intelligence.

Taking the IT industry as an example:

Application vendors, such as ERP, CRM, and industry application providers, can quickly embed agile business intelligence tools to provide customers with more value-added services.

Project risks of implementers and business intelligence are greatly reduced, project cycle is greatly shortened, and results are delivered quickly.

Agile business intelligence has been relatively mature abroad, but so far, yonghong is the only domestic agile business intelligence tool.

This is a new revolution. In The Big Data era, countless data miners have emerged and some people need to provide a shovel.

650) This. width = 650; "src =" http://s2.sinaimg.cn/large/003cZYBezy6KaUWLpstf1 "style =" border: 0px; margin: 5px auto 0px; padding: 0px 0px 5px; "alt =" 003czybezy6kauwlpstf1 "/>

This article is from the agile Bi blog, please be sure to keep this source http://9220305.blog.51cto.com/9210305/1531558