The Topics You Have Know About Data Analyst To Learn Data Analyst in 2023


  •  DATA ANALYST

The Topics You Have Know About Data Analyst To Learn Data Analyst in 2023

Data Analyst is the study of data, where we apply statistical techniques and extract

insights from the data which helps organizations in better informed decision making

  • Course Content

  • Introduction to Data ANALYST


  1. Why? What? How?. Role and Responsibilities of Data Analyst
  2. Data science vs Data Analyst vs Data engineer

  • Introduction to Excel

  • Introduction
  • Data Preparation & Data Modules Fundamentals
  • Data Preparation & Visualization               Advanced-Templates,R scripting Tooltips
  • Intermediate Data Transformation             Para meters & Functions  
  • Intermediate Inter Active Visualization     DAX - The Essentials
  • Intermediate Data Transformation             DAX - Advanced
  • Intermediate Inter Active Visualization
  • Advanced Visualization

  • SQL

  1. Introduction & Installation
  2. DDL - Create, Alter, Drop & Truncate
  3. DML - Insert, DQL - Select
  4. DML - Update, Delete, Where Clause, Import Data, Export Data
  5. Operators - Arithmetic, Comparison, Logical - And, Or, Not
  6. Operators - Between, Like, Wildcard, RegExp Is Null, Is Not Null In, Distinct, Limit
  7. Aggregate Function - SUM, MIN, MAX, COUNT, AVG, ROUND, STD, SQUARE,
  8. POWER, FLOOR, CEILING
  9. Order By, Group By, Having, Alias, Clone Table, Views, Subquery, Handling
  10. Duplicates
  11. Date Function - CURDATE, ADDDATE, ADDTIME, CURTIME, DATE_FORMAT, NOW,
  12. MONTH, MONTHNAME, DAY, EXTRACT, DAY, DAYOFMONTH, DAYOFWEEK,
  13. DAYOFYEAR,, DATEDIFF
  14. Joins - Inner Join, Left Join, Right Join Using Function
  15. TCL - SavePoint, Rollback, Commit Constraints - Primary Key, Foreign Key, Null,
  16. Not Null, Unique, Auto_Increment
  17. DCL - Grant, Revoke Create User, Alter User, Drop User
  18. Store Procedure, Index, SQL Injection, Windows Function

  • Power BI

                  Topic

Understanding Power BI

Download & Install

The Three Views In Power BI

Important: Initial Settings

Query Editor - Basic data cleaning

Working with the attached project files

Edit rows & columns,Data Types,Replacing ValuesData Types, Replace & Edit rows

Data Preparation & Data Modules Fundamentals

Extracting values,Split columns,Text operations,Numerical operations

Creating relationships (data model)

Stacked column chart & Pie chart

Data Preparation & Visualization

Append Queries, Merge & Group, Dates & Hierarchies, Line Chart

Files from a folder, Fact-Dimension modelEdit relationships & cardinality

Activate & deactivate relationships

Manage & autodetect relationships

Intermediate Data Transformation

Tables, Customizing tables, Merging Queries, Unpivot & Pivot&Many-to-Many Relationship,

Filter Visual

Intermediate Inter Active VisualizationFilters Pane, Top N Filter,]Sync Slicers, Treemap

Visuals, Edit interactions, Drillthroughs, Keep filters with drill through, Tooltips

Custom column, Enable & Disable Load, References vs. Duplicates. Columns from example

Advanced Visualization

Visual Header & Sorting, Conditional Coloum, Maps, filled maps,Forecast

Drill Through with Button, Books marks, Top products,Cards, Multi Row Cards

Power BI

     Topics       

Para meters & Functions

Get data from a web page, Use parameters with a web page   

Understanding Calculated Columns, Understanding,

MeasuresAVERAGE, COUNT, DISTINCT COUNT, COUNTROWS

SUM,AVERAGEX & ROUND

RELATED & Data Model, CALCULATE,Filter problems

FILTER

 Logical operato

 DAX - Advanced

ALL

ALL on columns

ALL EXCEPT

ALL SELECTED

DATEADD 

Year-to-Date & Month-to-Date

ROUNDING functions

FORMAT

DATA ANALYST


 Python


1. Introduction to Python for Data Science                           24. Membership Operators

2. Install and Write Your First Python Code                         25. If Statement  

3. Introduction to Jupyter Notebook And Jupyter Lab         26. If...Else Statement

4. Keywords And Identifiers                                                27. ELif Statement

5. Python Comments                                                            28. For loop  

6. Python Variables                                                               29. While loop 

7. Rules and Naming Conventions for Python                     30. Break and Continue Statement 

   Variables                                                                            31. User Define Functions    

8. Integer & Floating Point Numbers                           32. Arbitrary Arguments 

9. Complex Numbers                                                            33. Function With Loops  

10. Strings                                                                             34. Lambda Function 

11. LIST                                                                                35. Built-In Function 

12. Tuple                                                                               36. Global Variable

13. Set                                                                                   37. Local Variable

14. Dictionary                                                                       38. File Handling in Python  

15. Range In Python                                                             39. The Close Method  

16. List Comprehension                                                       40. The With Statement 

17. Input() Function In Python                                             41. Writing To A File In Python 

18. Arithmetic Operators                                                      42. Python Modules  

19. Comparison Operators                                                   43. Renaming Modules 

20. Logical Operators                                                           44. The from...import Statement  

21. Bitwise Operators                                                           45. Python Packages and Libraries 

22. Assignment Operators                                                    46. PIP Install Python Libraries

23. Special Operators                                 


PYTHON NUMPY                                                PYTHON PANDAS


1. Introduction To Numpy                              1. Pandas- Series   

2. Creating Multi-Dimensional Numpy         2. Loc & iLoc

Arrays                                                             3. Operations On Pandas DataFrame   

3. Arange Function                                         4. Selection And Indexing On Pandas DataFrame

4. Zeros, Ones and Eye functions                  5. Reading A Dataset Into Pandas DataFrame

5. Reshape Function                                      6. Adding A Column To Pandas DataFrame

6. Linspace                                                    7. How To Drop Columns And Rows In Pandas DataFrame

7. Resize Function                                        8. How To Reset Index In Pandas Dataframe  

8. Indexing & Slicing                           9. How To Rename A Column In Pandas Dataframe

9. Broadcasting                                            10. Tail(), Column and Index  

10. How To Create A Copy Dataset             11. How To Check For Missing Values or Null Values(isnull() Vs Isna())                              

11. Introduction Creating Matrix                 12. Pandas Describe Function

                                                                     13. Conditional Selection With Pandas

                                                                     14. How To Deal With Null Values

                                                                     15. How To Sort Values In Pandas

                                                                     16. Pandas Groupby

                                                                     17. Count() & Value_Count()

                                                                     18. Concatenate Function

                                                                     19. Join & Merge(Creating Dataset)

                                                                     20. Pandas-Join

                                                                     21. Pandas- Merge      

  • DATA ANALYST

  • DATA VISUALISATION: MATPLOTLIB AND SEABORN

  1.  Matplotlib Subplots
  2.  Seborn
  3.  Scatterplot
  4.  Correlation
  5.  Boxplot
  6.  Pie Chart
  7.  Heatmap
  8.  Univariate Plots
  9.  Bivariate Plots
  10.  Multivariate Data Visualisation
    • Duration: 60 HRS (Project-Based Learning)
  • Questions?
 1, What qualifications do I need to be a data analyst?
    From domain expertise to various tools, here's all you need to become a data analyst.
    Degree and Domain Expertise. ...
    Knowledge of Programming. ...
    Knowledge of Data Analysis Tools. ...
    Understanding of Statistics and Machine Learning Algorithms. ...
    Knowledge of Data Visualization Tools.

 2,   What does a data analyst do?
     A data analyst reviews data to identify key insights into a business's customers and ways the          data  can be used to solve problems. They also communicate this information to company                leadership and other stakeholders.

 3,   Is data analyst a hard skill?
    Data analysis is neither a “hard” nor “soft” skill but is instead a process that involves a                  combination of both. Some of the technical skills that a data analyst must know include                  programming languages like Python, database tools like Excel, and data visualization tools like      Tableau.

 4,  Does data analyst require coding?
   Do Data Analysts Code? Some Data Analysts do have to code as part of their day-to-day work, 
   but coding skills are not typically required for jobs in data analysis.

  • Stay Tuned For More Blogs And Updates.....

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