SAS certification and data mining, what is commercial intelligent career development to data mining and business intelligence? Words related to data mining include, for example, data warehouses, Data Mining, Data Mining, Customer Relationship Management (CRM), SAS, PeopleSoft, SAP, etc. By the 1990s, online analysis processing system (OLTP) for data storage has developed quite mature, and the application of relational databases has been very popular, large enterprises or departments have accumulated a large number of raw data. These data are in accordance with relational structural storage, perform excellent in terms of update, deletion, and efficient storage (less redundant data), but in complex query efficiency is very low. To make full use of existing data, provide complex queries, provide better decision support, and data warehouse has occurred. The difference between data warehouse and database (database index relational database here) is that the data warehouse is convenient for inquiry (called the subject), breaking the standard generic constraint in relational database theory, reorganization and finishing database data , Provide data support for query, report, online analysis, etc. After the data warehouse is established, regular data loading (ETL) is a major daily work in the data warehouse system. At the same time as the development of data warehouse, a technique that found implies knowledge from a large amount of data is also raised in the academic field, which is data mining. Data mining is also known as the database knowledge discovery, which is to apply advanced intelligent computing technology to a large amount of data, allowing computers to discover potential, useful Mode (also known as knowledge). The initial data mining applications generally need to do with the organization data, experience algorithm design (modeling), excavation, evaluation, improvement and other steps. Some of the organizational finishing data occupy most of the time, accounting for 80% of the entire data mining project. The real popularity of data mining is based on the successful application of the data warehouse. A well-designed data warehouse has made raw data to organize and transform, on this basis, and the in-depth mining is a matter of chapter. Data mining is an emerging product under the promotion of information explosion in recent years, which is a hot technology that extracts useful knowledge from massive data. Traditional trading system, the interconnected network technology and ERP system in the 1990s have produced a lot of data under increasingly cheap storage equipment. However, the data analysis and knowledge extraction technology combined with it did not progress in a long time, so that the large number of original data stored did not take advantage of "knowledge", "knowledge", forming "data, but in the ocean, knowledge of" knowledge "and forming data. The desert "such a strange phenomenon. Data Mining is a method and technology that is discovered from a large amount of data and extracts useful knowledge. Because it is closely related to the database, Knowledge Discovery IN Databases, KDDs. Data mining can not only learn existing knowledge, but also find unknown knowledge; the knowledge is "explicit", which can be understood and easy to store and apply, so it has received values in various fields. From the end of the 1980s to the extensive application in the late 1990s, commercial intelligence (BI) with data mining as cores has become a new favorite in IT and other industries. Current data mining applications are mainly concentrated in telecommunications (customer analysis), retail (sales forecast), agriculture (industry data forecast), network log (web custom), bank (customer fraud), electricity (customer call), biological (gene), The celestial (star classification), chemical, medicine, etc.
The problem that currently solves is typical in: database marketing, customer group division (Customer Segmentation & Classification), background analysis, Cross-Selling, etc. market analysis, and customer loss analysis (CREDIT scoring), fraud detection, etc., has been successful in many fields. If you visit the famous Amazon online bookstore (www.amazon.com), it will find that when you choose a book, the relevant number of recommendations will appear "Customers Whon Bought this book also bought", which is the data mining technology effect. When it comes to data mining, it is not necessary to make business intelligence, referred to as BI, is to apply intelligent computing technology to traditional business sectors, thereby improving data analysis capabilities, optimizing business processes, and improving corporate competitiveness. Although the popularity of commercial intelligence is just a few years, it has penetrated into various industries and fields such as finance, telecommunications, retail, medicine, manufacturing, and governments, and become an important part of the business decision-making of large and medium-sized enterprises. Data mining is a technology that makes a lot of algorithms, such as decision tree, clustering, association algorithm, classification algorithm, neural network, etc., these algorithms can have a variety of implementations. Data mining penetrates to certain industries, producing some specific applications, such as customer relationship management, Customer Relationship Management, CRM, often hear. The concept of customer relationship management has been previously, but modern customer relationship management generally refers to a class of business intelligence applications for customer data as handling objects. By tapping customer information, discovering potential consumption trends or trends. For example, telecommunications companies develop different billing programs by analyzing user call modes (call time, time period, handle volume, etc.) to meet users while improving their profits. According to IDC's investigation and analysis of 62 business intelligence technology in Europe and North America found that the 3-year average daily return on investment in these enterprises was 401%, of which 25% of the company's return on investment exceeded 600%. The findings also show that a company wants to succeed in a complex environment, high-level managers must be able to control extremely complex business structures, and it is difficult to do if there is no detailed facts and data support. Therefore, as data mining technology is constantly improving and increasing, it will be used more users to get more managers to get more business intelligence. Data mining and business intelligence development prospects Plan a personal career development, there are two in many considerations that are very important: the development phase of the technology to be investing and whether it is expertise. Each technique has a certain development cycle from proposing a wide application (or failure), called the life cycle of science and technology. This cycle is roughly divided into innovative, Early Adopters, Differences (CHASM), Early Majority, late epidemics, and decay phase (Laggards). For application-type technicians, early popular phases are the best time to enter a new technical field, as this technology has passed the test of divergence, but also in the rising phase, the risk is the least, and it is easier to stand out. Data mining technology is now in such an early epidemic phase.
The object of data mining is data accumulated in a professional field; the mining process is a human computer interaction, multiple repeated processes; the results of excavation should be applied to this major. Therefore, the entire process of data mining is inseparable from expertise in the application. "Business First, Technique Second" is the characteristics of data mining. Therefore, learning data mining does not mean discarding the original expertise and experience. On the contrary, there are other industries, which is a major advantage for data mining. If you have experience in sales, finance, machinery, manufacturing, Call Center, through learning data mining, you can upgrade your career level. If you do not change the original professional, you will change from the original transaction role to the analytical role. Gartner has enumerated five key technologies that will have important impacts in 3-5 years in 2000, of which KDD and artificial intelligence rank first. At the same time, this report will be parallel computer architecture research and KDD into 10 new technical fields that should invest in the next five years: broadband, wireless, Linux, content management, real-time analysis, data mining, security, middleware, certification skills , Business intelligence and knowledge management. According to IDC (INTERNATIONAL DATA CORPORATION), it is estimated that the BI industry market is $ 14 billion in 2004. Now, with my country's joining WTO, my country will gradually be open to many fields, such as finance, insurance, etc., which means that many companies will face huge competitive pressure from international large-scale multinational companies. The level of business intelligence has been far more than my country. The US Palo Alto Management Group has conducted an investigation in the adoption of business intelligence technology of 375 large and medium-sized enterprises in Europe, North America and Japan in 1999. The results show that the application level of business intelligence technology has reached or approximately 70% in the financial sector, and in the marketing field, and in the next three years, the adoption level of the technology will increase by 50 in the fields in the future. %. Now, many companies see data as valuable wealth, and use business intelligence to find hidden information, and get huge returns. There is no official market statistical analysis report on the data mining industry itself, but domestic data mining has a certain study in various industries. According to foreign experts, in the next 5-10 years, with the increasing accumulation of data and the wide application of computers, data mining will form an industry in China. As we all know, IT employment market competition has been quite fierce, and the employment of the above data processing series is an unprecedented emphasis on the core technology of the data processing - data mining. Data mining and commercial intelligence technology is located in the pyramid tower of the entire enterprise IT-business architecture. At present, the domestic data mining professional talents are not yet perfect. It is very proficient in data mining technology in the talent market. The supply of commercial intelligence is extremely small, and the other Aspects of enterprises, government agencies and scientific research units have greatly demanded potential demand for such talents, and the supply and demand gap is extremely large. If data mining technology is combined with individuals already have expertise, you will open up a career! Getting SAS Global Professional Certification will help you have 269 offices around the world, SAS customers are located in 112 countries around the world, including 96% of Fortune 500 in 2003 and 98 companies in 2003. There are 4 million users worldwide. According to IDC statistics, SAS has accounted for 36.4% of the market share in 2001 statistical analysis and data mining software.
