Author: Zen and the Art of Computer Programming
The term "data-driven" has been widely used in all walks of life. Nowadays, with the rise of the Internet and mobile Internet, there are more and more data information, and data acquisition, processing, storage, and utilization are becoming more and more convenient. . So how to effectively use data for decision-making and management? How can we gain insights into businesses, products, and customers more quickly and improve work efficiency? This article will share some professional data analysis methods and application cases to help readers better understand the importance of data-driven and master the core skills in the field of data analysis.
2. Explanation of basic concepts and terms
Data: From any point of view, it refers to the quantity or quality of objectively existing things. For example: sales data, market data, economic data, customer data, competitor data, etc.;
Quantitative analysis: the method of converting raw data into calculable numbers, and performing statistics and analysis. Including data acquisition, data cleaning, data processing, data modeling, data mining and other links. Quantitative analysis can predict, predict and improve all phenomena and events in the real world. The scope of application of quantitative analysis is very wide, including finance, economy, society, medical care, manufacturing and other fields;
Data analysis: The research, arrangement and presentation of data is an important part of quantitative analysis. Including data integration, structuring, classification, screening, association, analysis, summary, visualization and other processes. Data analysis is often used in enterprise decision support, management decision-making, product development, marketing promotion and other links. The purpose of data analysis is not purely to obtain income, but to obtain better business value and brand image. Data analysis can help companies better understand consumer behavior habits, improve marketing effects, and optimize business strategies.
Data-driven leadership: The value of data is not only reflected in the fact that it can directly affect the performance of products and services, but also reflect the development direction of individuals, organizations, and countries, and even change the entire industrial chain. By analyzing the data, it can help the team improve their professionalism and enhance team cohesion&#x