Programming Languages

Data mining and data analysis are not the same, data analysis can be completed using some ready-made analytical tools, but the vast majority of the data mining to rely on programming, in the field of data mining commonly used programming languages such as R, Python, C + + +, java, etc., R and python are the most popular.

Big Data Processing Framework

Doing data mining inevitably have to come into contact with big data, at present, the commonly used big data framework on two, Hadoop and Spark, Hadoop's native development language is Java, more information, Spark's native development The native development language of Hadoop is Java, with a lot of information, and the native development language of Spark is Scala, but there is also a Python API.

Database Knowledge

This does not need to be said much, since it is to deal with the data, the knowledge of the database is naturally less, and the knowledge of common relational and non-relational databases must be mastered, and if you want to deal with the big

Data Structures and Algorithms

Data Structures and Algorithms

Savvy data structures and algorithms are quite important to data mining, and they are also asked for in the interviews for data mining positions. Data structures include arrays, chained lists, stacks, queues, trees, hash tables, sets, etc., while common algorithms include sorting, searching, dynamic programming, recursion, etc.

Machine Learning/Deep Learning

Machine learning is one of the most important parts of data mining. Machine learning algorithms build mathematical models of sample data to make predictions or decisions. Deep learning is part of a broader family of machine learning methods. This part of the study is divided into two main pieces: mastering the principles of common machine learning algorithms, and applying these algorithms and solving problems.

Knowledge of Statistics

Data mining is an interdisciplinary subject that involves not only programming and computer science, but also several fields of science, and statistics is an inaccessible part of the process, helping us to identify problems faster and distinguish between causality and correlation.

About what skills are needed for data mining, Aoto has shared with you. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to know more about data analyst, big data engineer skills and materials, you can click on other articles on this site to learn.