Data Analyst (Batch-04) Certification Program – Zero to Hero in Excel, SQL, Power BI & Python

Categories: MS Excel, Power BI, Python, SQL
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About Course

Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

 

Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education.

 

The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data, but be able to provide insight and analysis through clear visual, written and verbal communication.

 

Some responsibilities of a data analyst includes:

  • Developing records management processes and policies
  • identify areas to increase efficiency and automation of processes
  • set up and maintain automated data processes
  • identify, evaluate and implement external services and tools to support data validation and cleansing
  • produce and track key performance indicators
  • develop and support reporting processes
  • monitor and audit data quality
  • liaise with internal and external clients to fully understand data content
  • gather, understand and document detailed business requirements using appropriate tools and techniques
  • design and carry out surveys and analyse survey data
  • manipulate, analyse and interpret complex data sets relating to the employer’s business
  • prepare reports for internal and external audiences using business analytics reporting tools
  • create data dashboards, graphs and visualisations
  • provide sector and competitor benchmarking
  • mine and analyse large datasets, draw valid inferences and present them successfully to management using a reporting tool

 

In this course we will perform some task of a Data Analyst  using Python ,Excel, SQL, and  Power BI.  We will connect to a variety of data sources, perform  data transformation ,cleaning and  exploration . We will create dashboards to visual data

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What Will You Learn?

  • Retrieve and Filter data using basic and intermediate SQL syntax
  • Transform data with the help of Numerical, Date, and Text functions
  • Identify strategies for constructing an unbiased sample
  • Understand essential terminology related to SQL, databases, and data warehouses
  • Manipulating the values with functions
  • Building Advance functions and queries
  • Execute complex queries using Joins and Subqueries
  • Develop responses based on evolving requirements from the Business
  • Define and recognize the key branches of Statistics
  • Identify the various approaches to Inferential Statistics and their strengths and weaknesses
  • Identify strategies for constructing an Unbiased Hypothesis test
  • Assemble and perform a two-tail t-test
  • Create Professional-Grade Business Intelligence Reports from Scratch.
  • Extract, Transform (ETL) and Merge Raw Data into Visually Appealing Interactive Dashboards.
  • Utilize the Tools employed by Professional Analysts and Data Scientists in your Designs.
  • Master Data Analysis Expressions (DAX) for Power BI Desktop.
  • Demonstrate your proficiency through 03 Comprehensive Course Projects, Complete with Step-by-Step Solutions.
  • Delve into Advanced Visualization Techniques and Build Corporate Level Dashboards
  • Benefit from the expertise of an Industry Professional and Microsoft MVP (Most Valuable Professional).
  • Acquire proficiency in the same Tools employed by Leading Analytics and Business Intelligence Professionals.
  • Analyze Real-World Projects and Business Intelligence use cases.
  • Write and execute Python code to create variables, generate outputs, apply various operators, and manipulate different types of data
  • Capture and transform data using Numpy and Pandas packages
  • Explore data through different statistical methods to gain a deeper understanding
  • Visualize data to share insights using the Matplotlib and Seaborn packages

Course Content

Class 01 – Introduction of Data Analytics

Class 02 – Introduction of Power BI – Power Query

Class 03 – Text Tools (Extract, Merge Columns, Split Columns, Format) | Number Tools (Statistics) | Reference Queries | Column Quality | Date Tools (Age, Time Series, Categorical)

Class 04 – Conditional Column | Column for Example | Date Tools (Substract Days) | Group By | Filtering and Sorting | Parameters

Class 05 – Append Queries | Select from Folder | Data Normalization Concept | Data Modelling

Class 06 – Data Modelling | Star & Snow Flake Schema | Data Formatting | DAX Calculated Columns – Text Functions (LEFT, RIGHT, UPPER, LOWER, CONCATENATE, &) | Date Functions (DAY, MONTH, YEAR, DATEDIFF, TODAY)

Class 07 – Text Function (SUBSTITUTE, FIND, SEARCH, Dynamic RIGHT, LEFT) | Date Functions (WEEKDAY, WEEKNUM) | Logical Operator | Logical Functions (IF, Nested IF)

Class 08 – Logical Functions (Nested IF, SWITCH, SWITCH with TRUE, AND, OR)

Class 09 – Measures | Implicit vs Explicit Measures | Filter Context | Filter Flow | Aggregation Functions (SUM, COUNT, COUNTROWS, AVERAGE, DISTINCTCOUNT, DIVIDE, MAX, MIN)

Class 10 – CALCULATE | ALL | FILTER Functions | Variables and Commenting

Class 11 – Iterator Functions (SUMX, AVERAGEX, MINX, MAXX) | Time Intelligence Functions (DATEADD, PREVIOUSMONTH, PREVIOUSYEAR, PREVIOUSQUARTER, SAMEPERIODLASTYEAR, DATESYTD, DATESMTD, DATESQTD, DATESINPERIOD)

Class 12 – Handling Errors | Data Visualization (Navigation Bar, Images, Card Visual, Visual Formatting)

Class 13 – Data Visualization (Line Chart, Forecasting, Reference Line, Bar Chart, KPI Charts, Donut Chart, Pie Chart)

Class 14 – Data Visualization (Visual, Page, Report Level Filters, Basic Filter, Advanced Filters, TOPN Filter | Table Visual | Matrix Visual | TOPN Cards Visual | Slicer | Area Chart)

Class 15 – Data Visualization (Guage Chart) | Drilling (Up, Down, Through) | Bookmarks | Page Navigation | Custom Tooltips | Conditional Formatting

Class 16 – Project 01 – Oodles of Noodles

Class 17 – Project 01 – Oodles of Noodles

Class 18 – Project 02 – Market Mindz

Class 19 – SQL – Introduction to Database | Clauses (SELECT, FROM, WHERE, GROUP BY Statements) | TOP N | TOP N PERCENT Keyword

Class 20 – SQL – Clauses (HAVING, ORDER BY) | SQL Order of Operations | Aggregation Functions (SUM, COUNT, AVG, MAX, MIN) | Numerical Functions (ROUND, CEILING, FLOOR) | Date Functions (DATENAME, MONTH, DATEDIFF, DATEADD) | String Functions (CONCAT, UPPER, LOWER, CHARINDEX, LEFT, RIGHT, LEN)

Class 21 – SQL – Comparison Operators | IS and IS NOT Function | Conditional Functions (AND, OR, IIF, CASE – WHEN, THEN) | ISNULL Function

Class 22 – SQL – JOINS (INNER, FULL/OUTER, LEFT, RIGHT) | ER Diagram | Facts vs Dimension Tables | Relationships in SQL | UNION for Appending Queries

Class 23 – SQL – LIKE Function | CREATE VIEWS | Sub Queries (Scalar Query, Multi Row Query)

Class 24 – Sub Queries (Derived Column in SELECT, Derived Table in FROM) | Windows Functions (OVER(), PARTITION BY, ROW NUMBER, RANK, DENSE RANK. LAG & LEAD)

Class 25 – Data Cleaning in MySQL

Class 26 – World Life Expectancy Project

Class 27 – Microsoft Excel – Introduction to Excel | Shortcuts | Fill Handle | Flash Fill | Sorting | Filtering | Grouping | Custom Sort | Hide and Deleting | Mathematical Calculation | Referencing (Relative, Absolute, Mixed)

Class 28 – Microsoft Excel – Numerical Functions in Excel | 3D Referencing | Text Functions | Logical Functions in Excel (IF, Nested IF, LET, SWITCH Functions)

Class 29 – Microsoft Excel – Conditional Functions in Excel (COUNTIFS, SUMIFS Functions) | Lookup Functions (LOOKUP, VLOOKUP, INDEX & MATCH, IFERROR) | Data Validation (Number, Text Length, List, Dynamic Criteria)

Class 30 – Microsoft Excel – Conditional Formatting in Excel (Basic to Advance Formatting) | Data Visualization with Excel Charts (Column, Bar, Line, Histogram, Pie, Donut, Tree Map, Combo Chart)

Class 31 – Introduction of Pivot Tables

Class 32 – Advanced Pivot Tables

Class 33 – Warehouse Project (Data Analysis and Dashboarding) using Pivot Tables

Class 34 – Interactive Human Resource (HR) Dashboard using Advanced Excel

Class 35 – Introduction of Python | Types of Variables | Numerical Functions | String Type and Functions

Class 36 – Python – Conditional Functions | List Functions

Class 37 – Python – For Loop | List of List Working

Class 38 – Pandas for Data Analysis – DataFrame Basics | Creating DataFrames

Class 39 – Pandas for Data Analysis – Reading and Writing CSV and Excel | Handling and Replacing Missing Data