The Development and Application of business intelligence

Thirty years ago, the New York Herald declared that an unfamiliar man was "the most important thinker after Newton, Darwin, Freud, and Einstein ". It was not until today that the Internet is prevalent that we read his books of the past and suddenly realized the greatness of this person. His name is Marshall McLuhan.

"With the advent of electronic technology, people have extended (or established in vitro) a living Central Nervous System ." In 1965, McLuhan wrote this sentence in the book "Understanding Media". From today's perspective, it is still an uncertain saying.

Yes. Today, the Internet is another way for us, people and enterprises. Artificial Electronic nerves are completely different from the protein nerves given by parents, and the evolutionary power of the two forces interconnection. Today, a large amount of data has been sent from electronic nerves. A few millions of years ago, humans did not consider the need to deal with such data in order to resist the storm and hunt for wild animals.

So the problem arises.

Confusion in data fog

There was no feeling in the early 1990s S. By the end of 1990s, people were able to see the data fog. In the 21st century, the fog was heavier. This is the case with you and me. The story of a common beverage store can be used as evidence.

Before June 1993, only beer, Coca-Cola, and Arctic Ocean soda were sold in the store. The shipping and shipping bosses wrote in an old book that the customers were all acquaintances. In 1995, the business was big, with semicolons opened everywhere, more drinks, more wine, and dozens of items sold. An automatic teller machine is installed in the store. Every transaction has to be played with a keyboard, which is a little troublesome and can save your mind. The accounts recorded on the ATM are printed every day to the boss. At first, the boss looked at it every day. It took a long time to see it. Just add the total number. The boss is still clear about how to do the business. In, the number of products operated was over. The store connected to the Internet and used financial software. In 1999, I went to the Internet again, with more shops around me growing every day, and guests from all directions. A thick pile of bills is made every day, and the boss is staring at the dense numbers, making it difficult to do business.

From
The boss of the beverage store has paid for the electronic nerves. The data sent above seems to be one day more than a day, and the meat nerves provided by his aunt need to be overloaded. In the past, the boss knew exactly what to sell, who to love, and what to enter.
How much goods and what goods to import. Now I have no idea about the exact but undefined figures. I don't know where the store is selling or what the customers like. Hand
People have a wide variety of ideas, and they are anxious to see the profits fall down. The digital tianchu is blindfolded, and the boss is wrapped in the fog of data.

Data fog is everywhere. The bigger the company is, the heavier the fog is. As a hotel, you cannot determine the average income of each room using semicolons (;) from all over the world. You cannot determine what type of guests are always there. In the end, you cannot determine your own market position. The increase in total data volume is staggering. The American MCI is a multinational telecommunications company with 0.2 billion million long-distance telephone customers and 5 TB of data stored in the computer, an increase of 300 GB per month. According to a study at a university in California, everyone in the world has produced or is about to generate 1010 MB of data, and the global data increases by 2 × GB each year.

How can we walk in the heavy fog? A converter can be installed between the electronic neural network and the meat neural network to convert the digital book into a color chart, a simple table, and general information. The meat neural network can understand the business status and make decisions. The converter between the two nerves and the lamp that guides us through the fog of data are "business intelligence ".

Intelligence in Business Intelligence

The concept of business intelligence (BI) was first proposed by Gartner Group in 1996, when the Internet was not so popular. At that time, business intelligence was defined as a major category of technologies and their applications that help enterprises make decisions and collect, store, analyze, and access data. At that time, Gartner Group predicted that by 2000, information democracy would emerge in enterprises with forward thinking. With Business Intelligence, employees, consultants, customers, suppliers, and the public can use information effectively. The technologies and applications involved in business intelligence are available before the Gartner Group name. As an internal information system of an enterprise, it was first called the execution Information System (EIS), which was called the Decision Support System (DSS) before its emergence into business intelligence ).

It should be appropriate to regard business intelligence as a solution, which contains a large number of technologies and application systems, and more technologies and applications are being integrated into business intelligence. The basic components of business intelligence solutions include data warehouses, data analysis, data mining, data presentation, and enterprise information portals. Businesses that are moving closer to business intelligence include ERP, CRM, Text Mining, knowledge management, Web Intelligence, wireless intelligence, competitive intelligence, and market intelligence.

Bill inmon, the father of the data warehouse, wrote in 1990: "data warehouse is a topic-oriented, integrated, time-changing, and never-lost data set to support management decision-making ." Data in a data warehouse is organized by topic based on metadata rather than the company's operating bills in a database. Data Warehouses integrate multiple data sources, including internal and external data of the company, and integrate it into a coherent whole. Data Warehouse is the data basis of business intelligence.

X coordinate: the time of day y coordinate: month Z coordinate: Sales Volume gray coordinate: Temperature

There are many data analysis methods in business intelligence, and OLAP (Online Analytical Processing) is the most popular nowadays ). This method can be used to extract and observe data from different angles and dimensions. For example, analysis and sales can generate a view from three dimensions: product, region, and time. What-If analysis (hypothesis analysis) is another standard method that can be used to create data models for departments or enterprises. When making a decision, input the parameter, which is simulated and predicted by the system based on historical data. The third common cause is ANOVA analysis (Change Analysis ). It can be used to identify the real cause of the problem from multiple possibilities and is widely used in the manufacturing industry. Data mining is also a data analysis method. It aims to find potential trends in historical data, so that enterprises can learn and predict the future in the memory.

There are also many ways to present data in business intelligence. Pre-designed standard reports can provide data in a fixed format in electronic and paper forms; structured reports allow users to make certain changes to the format and data items; special reports can be extracted and formatted as required by users. OLAP usually displays the data as a three-dimensional color chart. Exceptional reports summarize the data that exceeds the specified value and output it as an alarm.

The Enterprise Information Portal (EIP) has evolved into a standard component of business intelligence. EIP provides a unified, web-based, and easy-to-integrate interface for multiple data sources and application systems for Business Intelligence solutions.

Data fog is the feed of business intelligence. The greater the fog, the more Bi, the more powerful. In the 1980s S, commercial systems only output reports printed on paper. In early 1990s, the fog was heavy and the sales department used a data warehouse to answer questions like who the top 10 customers are and what the target market is. By the end of 1990s, not only the sales department, marketing department, customer service department, and even the R & D department wanted to become bi users, but business intelligence had grown into a public platform for enterprises. In this century, it is not enough to use Bi only for internal business operations. People need it to analyze customer behavior, market trend, competitors and partners.

Business Intelligence has evolved from a department-level application to an enterprise-level application, and is evolving from an internal application to a global application.

Smart Market View

Since the beginning of this century, the business intelligence market has been quite lively.

In June this year, Dataquest said its global database sales last year were $8.8 billion, and earlier reports predicted that the global sales in the business intelligence market could reach $6.2 billion next year. The database market has seen an annual growth rate of around 20% in recent years, and business intelligence has exceeded 35%. Now, the business intelligence market is almost the same as that of databases, and it will take less than two years. How can a powerful company ignore such a huge market? There are dozens of Bi vendors in the U.S. market for several years. Now the domestic voice is still small. In a few months, media vendors may make your eyes full of Bi.

Last year, Gartner Group studied and divided the suppliers of business intelligence systems into two camps: leaders and challengers. The leaders are all small and well-known companies, such as alphabrov, Cognos, and crystal. These companies entered the Bi market earlier, with complete product functions and many users. They provide comprehensive data analysis and presentation tools, including what-if analysis and OLAP. These business intelligence platforms must be built on third-party data warehouses.

Gartner Group lists Oracle, CA, SAP, SAS, and Microsoft as challengers. These companies have their own traditional databases, data warehouses, and even ERP and CRM solutions. Now they are building or strengthening data analysis and presentation platforms. Oracle not only supports databases, data warehouses, CRM, and ERP, but also provides financial/sales analysis. In addition to data warehouses, SAP also provides financial/Human Resource Analysis, CRM, and supply chain management solutions. These companies entered the Bi market a little later and their products were not perfect enough. When providing BI solutions, they needed to integrate the first-camp products. Although companies such as IBM, HP, Compaq, Sybase, and infomix are not shortlisted in the report, they are also providing BI solutions to customers.

Since the beginning of this year, domestic banks have already put their BI systems into operation, and their telecommunications systems have also held seminars. However, they are mainly promoted by foreign manufacturers. In fact, the data analysis and display tools in Bi are suitable for small companies. I believe that Chinese companies will soon join this trend.

Electronic nerves grow and spread outside of you without knowing it, and the data fog is thicker than a moment. If one day you lose yourself in a mall, don't forget: lighting up business intelligence.