Data mining refers to the process of mining unknown, and valuable information and knowledge from a large amount of data, through statistics, artificial intelligence, machine learning and other methods. Data mining mainly focuses on solving four types of problems: classification, clustering, correlation and prediction, that is, quantitative and qualitative, data mining focuses on finding unknown patterns and laws. Output models or rules, and can get model scores or labels accordingly, model scores such as churn probability value, sum score, similarity, predictive value, etc., labels such as high school and low value users, churn and non-churn, good credit, medium and poor credit, etc.. It is mainly mined using statistical, artificial intelligence, and machine learning methods such as decision trees, neural networks, association rules, and cluster analysis. Taken together, the essence of data analytics (in the narrow sense) and data mining are the same, both are discovering knowledge about the business (valuable information) from inside the data, which can help business operations, improve products, and help companies make better decisions, so data analytics (in the narrow sense) and data mining constitute data analytics in the broad sense. These elements are not the same as data analytics.
Applications and Career Fields
Current data mining applications are focused on telecom (customer analytics), retail (sales forecasting), agriculture (industry data forecasting), weblogs (web page customization), banking (customer fraud), power (customer calls), biology (genetics), astrobiology (astral classification), chemicals, pharmaceuticals, and so on.
Currently it can solve the problem typically lies in: database marketing (Database Marketing), customer group division (Customer Segmentation & Classification), background analysis (Profile Analysis), cross-selling (Cross-selling) and other market analysis. selling) and other market analysis behavior, as well as customer churn analysis (Churn Analysis), customer credit scoring (Credit Scoring), fraud detection (Fraud Detection) and so on, has been successfully applied in many fields.
Career Salary
As of now, like most of the IT industry positions, the demand for data mining talent in the country's demand for work is saturated at the low end, the high-end shortage. From the recruitment of BAT, the field of data mining is relatively high threshold, but the salary and benefits are also relatively good, common such as Tencent, Ali will give to the annual salary of 20W +. And powerful senior algorithm experts annual salary of one million is also a common thing, so everyone in the algorithm is still a big possibility. In addition, as finance is becoming more and more Internet-based, a large number of algorithm engineers will become the shortage of Internet finance companies in the future.
Want to know more about data mining related information can consult the CDA data analyst
CDA (Certified Data Analyst), also known as "CDA data analyst", refers to the Internet, retail, CDA (Certified Data Analyst), also known as "CDA data analyst", refers to a new type of data analyst who specializes in data collection, cleaning, processing, analysis, and production of business reports and decision-making in the Internet, retail, finance, telecommunications, healthcare, tourism and other industries. It aims to strengthen the construction of formalized, scientific and professional big data and data analytics talent team worldwide, further enhance the professionalism and competence level of data analysts, and promote the high-quality, sustainable and rapid development of the data analytics industry.
"CDA Data Analyst Certification" is a set of professional, scientific, internationalized and systematic talent assessment standards, divided into CDA LEVEL Ⅰ, LEVEL Ⅱ, LEVEL Ⅲ, involving finance, e-commerce, medical, Internet, telecommunications and other industries, big data and data analysis practitioners need to have the skills, in line with today's global big data and data analysis practitioners. It covers the skills needed by big data and data analysis practitioners in finance, e-commerce, healthcare, Internet, telecom and other industries, and is in line with the current trend of global big data and data analysis technology, providing a reference standard for data analysis talents for enterprises and organizations of all sectors.
"CDA Data Analyst Training" is a professional, scientific and systematic learning program based on the standards of CDA Data Analyst Certification System. The training content not only includes the skills and knowledge requirements of the certification standards, but also real projects and cases in the corporate environment, which can meet the needs of students at different levels, so that students can learn the real skills and be able to apply them to realize the business value.
To learn more about data analyst issues, you can consult the CDA certification center. Global CDA licensees adhering to the new concept of advanced business data analysis, follow the "CDA Code of Ethics and Conduct" new norms, play their own data expertise, promote the progress of scientific and technological innovation, and contribute to the sustainable development of the economy.