Business Intelligence = Data + Analytics + Decision + Benefits

Business Intelligence = Data + Analytics + Decision + Benefits

First, Background introduction

The human society, from barter to the creation of money, to a variety of transactions, has produced all kinds of commercial activities that are now flourishing and complex. Interest is the core of business, and business needs to pass through the buyers and sellers of the transaction, negotiation, and the flow of goods need logistics, inventory, which business process is very cumbersome, but the progress of science and technology improvement or is changing its form, people's efficiency is greatly improved.

In this information era, many traditional businesses are replaced by information technology or information technology as its auxiliary means. So, in this era, all people are talking about data, and the relevant business data is exploding exponentially. However, not all of the data is useful, so people need to dig into useful information to guide the real work.

Business intelligence, in English, is Intelligence, abbreviated as BI. Business intelligence is often understood as a tool to transform existing data in an enterprise into knowledge and to help companies make informed business decisions. For example, the department stores every day a variety of goods are sold, its POS system stores the sales of goods, data is very large. From this data, we use certain mathematical models and intelligent software tools for analysis, to know which products are the best sellers and what times people like to buy. Then, using the results of the analysis to make decisions, such as analysis that beer and fried chicken sold more during the rainy days than in other weather periods, we decided to increase the production of beer and fried chicken on rainy days. Through these analysis and decision-making, we have increased commercial profits, which is our power to use modern tools for business intelligence. This process can be summed up as one of the following equations:

Business Intelligence = data + Analytics + decision + Benefits

Second, data acquisition

Traditional data acquisition is manual paper records, the disadvantage is that the record error-prone, and over time, the number will be greatly increased so that the difficulty of finding historical data. For example, the traditional landlord's housekeeper carries on the family financial registration, the ledger is thick and heavy, the account is extremely troublesome, and perhaps the ledger may be damaged by the fire or various reasons, such as by the mouse bites rotten.

With the advancement of technology, with computers, data is stored on tapes and then disks. The world has a division of labor and wonderful, everyone in their own areas of expertise to work, thereby creating greater benefits. So, do not understand the computer's small partners with the help of others developed management system for data management, such as supermarket commodity management system, the company's internal personnel management system. And the software programmer through the database, data warehouse and other products to design code, created the above management system.

So, a layer of relay layer, data acquisition from a manual pen down to use a computer keyboard to enter. By means of modern technology, viewing historical data as long as the search is done, it is very good to get the data from ten years ago, so that data can be analyzed more efficiently.

Business intelligence, intelligent two words highlight the importance of computers. Everything on the computer is made up of 0,1 binaries , two of the most common symbols that build the entire data building of the computer. How to better save the data to the computer disk, and quickly read it out? Early data storage was the use of cards to read data, and later produced a modern computer storage system, registers, memory, disk. Starting from the hardware, the software-level file system,IO Stream, was later presented . In order to more convenient storage of large amounts of data, the emergence of database software, a variety of database theory and tools began to appear.

Currently the most used database is the relational database proposed by 1993 e.f.codd.

Third, data analysis

Data analysis relies primarily on data mining knowledge, as business intelligence is a branch of data mining. Data mining generally refers to the process of searching the information hidden in a large amount of data through an algorithm. Data mining is often related to computer science and is achieved by means of statistics, online analytical processing, information retrieval, machine learning, expert systems (relying on past rules of thumb), and pattern recognition.

Data mining utilizes ideas from the following areas:(1) sampling, estimating and hypothesis testing from statistics,(2) Artificial intelligence, pattern recognition and machine learning search algorithms, modeling techniques, and learning theory. Data mining also quickly embraced ideas from other areas, including optimization, evolutionary computing, information theory, signal processing, visualization, and retrieval. Some other areas also play an important supporting role. In particular, database systems are required to provide efficient storage, indexing, and query processing support. Technologies that originate from high-performance (parallel) computing are often important in dealing with massive datasets. Distributed technology can also help to process massive amounts of data, and it is critical when data is not centralized for processing.

The main analytical algorithms are the classification (classification) estimation(estimation) prediction (prediction) correlation Grouping or association rules ( Affinity Grouping or association rules) Clustering (clustering) and so on. These algorithms mainly rely on the building of mathematics, most of the commercial data mining software has realized these functions, convenient for ordinary people to use.

By using data mining software, the data stored in the database can be analyzed and processed, and some statistical and computational results are obtained. These results can guide realistic decisions.

Current data mining software for general analysis purposes with the package SAS Enterprise Miner,SPSS Clementine,IBM Intelligent Miner , Software KD1(for retail)Options & Choices(for the insurance industry) developed for specific functions or industries HNC unica Model 1(for marketing)IEM System (real-time historical data for the process industry) (for credit card fraud or bad debt detection) .

Iv. Business Decisions

With the development and application of database technology, the amount of data stored in database has been transitioning from trillion (M) bytes and Gigabit (G) bytes to current mega (T) bytes and gigabit megabytes (P ) Byte, at the same time, the user's query demand is more and more complex, involves not only to query or manipulate one or several records in a relational table, but also to the data analysis and information synthesis of thousands records in multiple tables, the relational database system can not fully meet this requirement. In foreign countries, many software manufacturers have taken the development of their front-end products to compensate for the lack of support of relational database management system, trying to unify dispersed public application logic and respond to the complex query requirements of non-data processing professionals in a short time.

The online analytical processing (OLAP) system is the most important application of the Data Warehouse system, which is designed to support complex analysis operations, focusing on decision-making support for decision-makers and senior management, and can be based on the requirements of analysts quickly, Flexibly perform complex query processing of large data volumes, and provide query results to decision makers in an intuitive and understandable manner so that they can accurately grasp the business status of the Enterprise (company), understand the needs of the object, and formulate the correct plan. .

Olaptools are online data access and analysis for specific issues. It analyzes, queries, and reports on data in a multidimensional way. Dimension is the specific angle at which people observe data. For example, when an enterprise considers the sales of a product, it usually takes a closer look at the sales of the product from different angles of time, region, and product. The time, region and product here are dimensions. andThe different combinations of these dimensions and the multidimensional arrays of the measured metrics that are examined areOLAPthe basis of the analysis, which can be formally represented as (dimensional1, Dimension2,..., DimensionN, metrics), such as (region, time, product, sales). Multidimensional analysis refers to the slicing of data organized in multidimensional form (Slice), diced (Dice),Drillthrough (Drill-downand theroll-up), Rotation (Pivot) and other analysis actions, in order to analyze the data, so that users can view the data in the database from multiple angles, multi-sided, so as to deeply understand the information contained in the data.

Business decision-making uses the above data mining software results, and OLAP is a more convenient system, faster and better display the results of the analysis in the form of charts and so on, convenient for decision-makers to compare and discuss. With the processing of intelligent tools, leaders and reformers can decide whether to conduct a business, or how to conduct a business, which is also called business decision-making.

Five, the interest motive force

The key to business intelligence is to extract useful data from a number of data from different enterprise operating systems and clean it up to ensure that the data is correct and then extracted (extraction ), conversion ( ) and load ( etl Span style= "font-family: the song Body;" > process, merged into an enterprise-level data warehouse, resulting in a global view of the enterprise data, based on the use of appropriate query and analysis tools, data mining tools, olap tools, etc. to analyze and process them (this time information into the knowledge of auxiliary decision-making), and finally the knowledge presented to the manager, the decision-making process for managers to provide support.

Business intelligence = Data + Analytics + decision + benefits, the equation contains benefits, because the benefits as a driving force, promote the development of business intelligence. Because want to change, so change. Because want to improve efficiency, so change. Because we want to make the best profit with the smallest investment, we should change it. The change of human life is the source of human's pursuit of a better life, to liberate mankind from the busy physical labor. Computer, a technological product, is connected with business and must create great value.

Vi. Summary

We can predict that in the future, business intelligence will flourish, singing all the way, this also for our individual and country to make a hint. Business intelligence is not mysterious, it is so simple, summed up is:

Business intelligence = Data + Analytics + decision + Benefits

Business Intelligence = Data + Analytics + Decision + Benefits