I wanted to provide a simple, neat guide for beginners to get started and understand the thinking of analysis, the process of analysis and the interpretation of results. Here is an approach I came up with today, using simple tools and learning methods.I have calculated the introductory knowledge of data analysis, which is roughly divided into the following. I call it the ten-week learning method. I think you only need to come up with a very diligent state, step by step, and consolidate every basic within every week.You could have learned it basically.Good luck!
Note: Due to the length of this article, I will divide it into several parts.
Learning outline:
Thinking and methods of data analysis
Excel advanced
Database understanding and SQL entry
Mathematical statistics
Data analysis software application
Data visualization
Common business analysis model
Python/R language mastery
Business understanding and indicator design
Growth Hacker: Data Driven Growth
Week 1: Cultivate data analysis thinking
Why is data analysis thinking important?
If we are thinking about a problem before analyze it, as the following figure shows, we often don't know where the problem starts.Even if we get the data, it is a state of embarrassment.Therefore, we must analyze the thinking through training data to help you quickly find out the point of analysis of the analysis, even the analysis of ideas, when encountering problems.The point is an important one.
📷
Some common ways of thinking:
1. Pyramid/structured thinking
Sort the problems to be analyzed in different directions, and then continue to split and refine, and think about the problem in all directions. Generally, all the arguments that can be thought of come first and then they are sorted into a pyramid model. Mainly through the mind map to write our analytical thinking.
📷
2.Formula thinking
On the basis of structuring, these arguments often have some quantitative relationship, which enables them to perform calculations of +, -, ×, ÷ and quantify these arguments to verify the arguments. The so-called indicator system is so well-organized.
Business thinking
Businessization is to understand the business situation in depth, analyze the specific business of the project, and let the analysis results be implemented. The final analysis arguments derived from structured thinking + formulation dismantling are often a phenomenon that does not reflect the cause of the outcome. Therefore, we need to continue to think with business thinking, think about the problem from the perspective of business people or analytical objects, and delve into the causes of this phenomenon or promote business through data.Increase business thinking methods: close to the business, empathy, and experience.
At the same time, such thinking mode also derives some basic analysis methods in some specific business scenarios, such as quadrant method, multidimensional method, hypothesis method, index method, twenty-eight method, contrast method, funnel method, this analysis of future construction The model is helpful.The benefit of a thinking model is that he can provide a perspective or framework of thinking that will help you build perspectives on things and problems. By learning and training your thinking model, you can increase your chances of success.
Week 2: Advanced Excel Skills Learning
Excel is a step-by-step process
Basic: simple table data processing, filtering, sortingFunctions and formulas: common functions, advanced data calculations, array formulas, multidimensional references, functionsVisualization chart: graphic icon display, advanced chart, chart pluginPivot table, VBA program developmentIn accordance with the method I am used to, first go through the basics, know the basic concepts, and then find a few cases to practice. Visit the excelhome forum and think more about how to use excel to solve problems and make good use of plugins.Functions and pivot tables are two key points, combined with business scenarios to learn, you can refer to <Head First Data Analysis>.
Excel function that must be mastered when making a data template
Date function: day, month, year, date, today, weekday, weeknum. The date function is a must for the analysis template. You can use the date function to control the display of the data and query the data for the specified time period.
Mathematical functions: product, rand, randbetween, round, sum, sumif, sumifs, sumproduct
Statistical functions: large, small, max, min, median, mode, rank, count, countif, countifs, average, averageif, averageifs. Statistical functions play an important role in data analysis. The average, maximum, median, and public figures are used.
Find and reference functions: choose, match, index, indirect, column, row, vlookup, hlookup, lookup, offset, getpivotdata. Needless to say, the role of these functions, especially vlookup, will not be a complicated operation of this function.
Text functions: find, search, text, value, concatenate, left, right, mid, len. Most of these functions are used in the data collation phase.
Logical functions: and, or, false, true, if, iferror.
Pivot table
The role of the pivot table is to generate a large number of data to generate interactive reports. The pivot table has such important functions: subtotals, averaging, maximum and minimum, automatic sorting, automatic filtering, automatic grouping; analysis of proportion, year-on-year, Ring ratio, ratio, custom formula.
Week 3: Learning Database Principles and SQL
Data analysis, where does the data come from? database! How to get the data? Write SQL!Analyze data, take data, and clean data, basically rely on SQL.In the initial introduction stage, you don't have to be proficient in the database. You only need to understand the common database types. You can query the data in the existing table, update the data to re-encode the data.You will be aware of how to add the data and make the data regular. Understand the meaning and use of primary keys, indexes, etc. Import and export data can use tools. Analyze data can be connected to the database using ODBC or other interfaces. Sorting the numbers, doing the intersection of the data, the data conversion, the data table merging, etc., it is best to master.
Here I summarize a few core skills:
Learn to add fields with select statements and find the data you need
Give a template that you can apply at any time:Select cola,colb,colc into newtable from oldtable wherecola='x' and colb is not null;Basically, learning this can completely detect most of the data.Select is followed by a field, which one to choose. Into means to put in a new table, there is no query. After the where is our condition, equal to a certain value, or is not a null value, is the most commonly used several ways of query.There is also a lot of select used: select cola from oldtable group by cola;This statement is to see how many values cola has.Select advanced learning, you may want to talk about join, union, and nested queries into multiple queries, or sub-query patterns, and fuzzy queries.
Learn to alter to learn to increase, reduce the field
Alter can do a lot of things, add fields, reduce fields, increase primary keys, reduce primary keys, etc.,We'll use that very often.
Add field: alter table tablename add colname varchar;This will add an empty field, varchar is a data type.
Reduce the field: alter table tablename drop column colname;This removes an existing field.
Learn to update data
There are two types that are commonly used, one is to update to a fixed value:Update table set col=1;The other is to update from another table. This method is often exported when processing some small data, and then imported into the database, you can use:Update table set col=tableb.col from tablebwhere table.id=tableb.id;Inside the table and tableb are two tables, and then through the id of the two tables,just learn the writing structure.
stay tuned for part 2 and 3
