How to get started with data analytics system? From basic to practical learning path

in the tide of digital transformation, data analytics system has become the core tool for enterprises to mine the value of data and drive business decisions. Many zero-based practitioners want to get started but don't know where to start, and often fall into the dilemma of learning fragmented knowledge but not being able to land. This article will build a clear learning path for you to start with data analytics system, help you avoid learning mistakes, quickly establish a system of knowledge, and gradually have the ability to use data analytics system to solve practical problems.

First, understand the core concepts of data analytics system

the first step in starting a data analytics system is to establish a basic understanding of it and avoid the problem of conceptual confusion in subsequent learning.

1, the core definition of data analytics system

data analytics system is a complete set of tools that integrate data collection, storage, processing, analysis and visualization. It can turn fragmented original data sources into valuable business insights. Different types of data analytics systems focus on different, some are biased towards data storage management, some focus on visual display, novice needs to clarify its overall framework first, and then focus on in-depth learning.

2, the core module of the data analytics system

common data analytics system includes four core modules: data collection layer, data storage layer, data analytics layer and data lake visualization layer. The data collection layer is responsible for integrating multi-source data, the data storage layer undertakes the classification and storage of data, the data analytics layer mines the value of data through algorithm models, and the data lake visualization layer converts the analysis results into intuitive charts. Only by cooperating with each module can a complete data analytics process be realized.

2. Master the practical operation of common tools of data analytics system

familiar with the core concepts of the data analytics system, you need to enter the practical operation stage of the tool, which is a key part of the entry, which can help you turn theory into practical operation ability.

1, entry-level data analytics system tools

zero-based beginners can start with easy-to-use tools, such as Excel as a lightweight data analytics system tool, which can meet the basic data cleaning, calculation and visualization needs, and is suitable for quickly establishing the operation feel. In addition, Tableau as a visualization tool can generate professional charts through drag and drop operations, helping beginners quickly understand the visualization logic of the data analytics system and lowering the learning threshold.

2, the core practice direction of tool practice

practical exercises should focus on the whole process of data processing. First, practice using data analytics system tools to complete data cleaning, such as removing duplicate values and completing missing data; then perform basic calculations, such as summation and average statistics; finally try to make histograms, line charts and other visual charts. By repeatedly practicing these basic operations, you can quickly familiarize yourself with the operation logic of the data analytics system and lay the foundation for subsequent actual combat.

three, with business scenarios landing data analytics system

master the basic tool operation, it is necessary to apply the data analytics system in combination with the actual business scenario, which is the core step of turning knowledge into capability.

1, choose close to their own business scenarios

novice can start from familiar scenarios, such as the analysis of user purchasing behavior in the e-commerce industry, or the learning data tracking of students in the education industry. After selecting the scenario, first clarify the business needs, such as analyzing the reasons for the low user repurchase rate, and then use the data analytics system to extract the corresponding data. According to the process of collection, processing, analysis and visualization, the learning is more targeted.

2, complete the whole process from demand to output

take the repurchase analysis of e-commerce users as an example, first use the data analytics system to collect the user's purchase time, product category, consumption amount and other data, then clean and remove the invalid data, and then find out the core problem by calculating the repurchase rate of different client bases. Finally, use a visual chart to show the correlation between the repurchase rate and the user's consumption frequency, form a complete analysis report, and truly realize the business landing of the data analytics system.

4. Advanced improvement of data analytics system application capabilities

when the basic business scenario analysis can be completed independently, it needs to be advanced to deepen the understanding and application ability of the data analytics system.

1, learn advanced functions of data analytics system

can start to touch the advanced features of the data analytics system, such as SQL language for complex data queries, Python data analytics library for automated analysis, or BI system multi-dimensional drill-through analysis. These features can help you deal with more complex business needs, improve the efficiency and depth of data analytics.

2, accumulate industry cases to optimize analytical thinking

learn more about data analytics system application cases in different industries, analyze the selection of data indicators in the case, the construction of analysis logic and the landing method of the results, and integrate these experiences into their own analytical thinking. At the same time, try to use different analysis methods for the same business needs, compare the differences in results, and gradually form their own data analytics system application ideas.

To sum up, the introduction of data analytics system is a gradual process from cognition to practical operation to actual combat. First clarify the core concepts and modules of the data analytics system, then establish the operation foundation through the practical operation of tools, and then complete the application in combination with business scenarios. Finally, advanced learning improves the depth of analysis. According to this path, you can quickly get rid of the zero basic state, and have the ability to solve practical business problems with data analytics system, laying a solid foundation for subsequent career development.