infyni

Mastering Data Analytics with Power BI & SQL & Python

Master data analytics with Power BI & SQL. Learn data manipulation, visualization, SQL querying, and integration for impactful insights.The course aims to up-skill you regardless of experience level.

Live Course

Live Class: Tuesday, 05 Dec

Duration: 20 Hours

Enrolled: 0

Offered by: infyni

Live Course
$1000 60% off

$400

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About Course

Unlock the potential of data analysis with our comprehensive course in Power BI and SQL. Dive into the world of data manipulation, visualization, and insights generation using Power BI. Learn SQL for data querying, manipulation, and database management. Master the integration of Power BI and SQL to extract, transform, and visualize data for informed decision-making. Join us to become proficient in leveraging data analytics tools for impactful insights.In this course, we will cover essential programming skills like SQL, Excel, PowerBI, ML, and Tableau The course includes hands-on experience with Python, MySQL,Excel Power BI, Tableau.

Skills You Will Gain

Power BI Fundamentals Data Import and Transformation in Power BI DAX (Data Analysis Expressions) SQL Basics Integration of Power BI with SQL Data Modeling and Relationships Creating Interactive Visualizations

Course Offerings

  • Instructor-led interactive classes
  • Clarify your doubts during class
  • Access recordings of the class
  • Attend on mobile or tablet
  • Live projects to practice
  • Case studies to learn from
  • Lifetime mentorship support
  • Industry specific curriculum
  • Certificate of completion
  • Employability opportunity
  • Topics
  • Instructor (1)
1 Introduction
  • Introduction to Power BI
  •  Get Data from Excel Files
  •  Get Data from Text Files
  •  Connect to SQL Server Database
  •  Creating first Tabular Report
  •  Creating first Column chart
  • Bar Chart
  • Clustered Bar Chart
  • Stacked Bar Chart
  • 100% Stacked Bar Chart
  • Column Chart
  • Clustered Column Chart
  • Stacked Column Chart
  • 100% Stacked Column Chart
  • Line Chart
  • Clustered Column and Line Chart
  • Line and Stacked Column Chart
  • Area Chart
  • Pie Chart
  • Donut Chart
  • Bins
  • Groups
  • Hierarchies
  • Basic Filters
  • Advanced Filters
  • Top N Filters
  • Filters on Measures
  • Page Level Filters
  • Report Level Filters
  • Slicer
  • Drill through Filters
  • merge queries
  • merge queries as new
  • append queries
  • append queries as new
  • enter data
  • changing data type
  • creating parameters
  • using parameters
  • use first row as headers
  • use header as first row
  • refreshing the data
  • replace values
  • choose columns
  • remove columns
  • keep rows
  • remove rows
  • group by
  • split column
  • trigonometry
  • rounding
  • information
  • transpose
  • reverse rows
  • count rows
  • scientific
  • standard
  • statistics
  • pivot
  • unpivot
  • extract
  • convert to list
  • format
  • conditional column
  • index column
  • duplicate column
  • Right click
  • Remove
  • Remove other column
  • Add column from examples
  • Remove duplicates
  • Remove errors
  • rename column
  • drill down as a new column
  • add a new query
  • Calculated Columns
  • Calculated Measures
  • Calculated Tables
  • Logical functions
  • Mathematical functions
  • Aggregation functions
  • Text functions
  • Date and time functions
  • Relationship functions
  • Table manipulation functions
  • Filter functions
  • Using the IF() function
  • Using the SWITCH() function
  • Fetching columns from another table with RELATED() Function
  • Introduction to ALL() and ALLEXCEPT() Functions
  • Introduction to VALUES() and DISTINCT() Functions
  • Understanding SUMX
  • Aggregating on a Filtered Table
  • Aggregation functions
  • COUNT, COUNTA, COUNTBLANK,DISTINCTCOUNT & COUNTROWS, AVERAGEX
  • How to expand filters with ALL() Function
  • Introduction to CALCULATE() function
  • Introduction to CALCULATE() function in Measures
  • Using CALCULATE() to filter multiple columns
  • Using OR Operator to filter multiple values from the same column
  • Using the IN Operator as an alternative to OR to filter values matching lists
  • Using ALL() as a filter argument in CALCULATE() expression
  • Understanding how ALL() filters columns in a DAX Measure
  • Creating a Date Table with CALENDARAUTO() Function
  • CALENDAR
  • Calculating Year to Date Values with CALCULATE() and DATESYTD()
  • Expanding DATESYTD Function with FILTER, DATEADD
  • Using TOTALYTD() to calculate Year to Date Values
  • Understanding RANKX() Function
  • Creating Top N Visuals using the Filters Pane
  • Calculating Top N Measures with TOPN() Function
  • Funnel Chart
  • Table
  • Matrix
  • Slicer
  • KPI
  • Card
  • Multi row card
  • Gauge
  • Map
  • Filled map
  • Treemap
  • Scatter chart
  • Waterfall chart
  • Ribbon chart
  • getting data from multiple sources of same type
  • getting data from multiple sources of different types
  • creating relations between tables
  • Understanding model cardinality
  • Import
  • Direct query
  • extract data using SQL query
  • Understanding Power BI service
  • Understanding Dashboard
  • Connect Desktop with Power BI Service
  • Create a Workspace
  • Create a Dashboard
  • Dashboard operations
  • Combining Reports to a Dashboard
  • Dashboard Settings
  • Delete a Dashboard
  • Pin Report to a Dashboard
  • power BI apps
  • Sharing and Collaboration
  • Sharing Apps, Dashboards, Workspaces
  • Publish to web
  • Data Warehousing
  • Dimensional modeling
  • Fact Tables
  • Dimension Tables
  • Hierarchies
  • STAR Schema
  • Snowflake schema
  • Slowly changing dimensions (SCDs)
  • Student's Live Hands-on, Questions, Answers
  • Database fundamentals
  • Database
  • Tables
  • Fields
  • Primary Key
  • Foreign Key
  • Relations
  • DQL, DML, DDL
  • Data types
  • Operators
  • Expressions
  • Create DB
  • Drop DB
  • Create Table
  • Truncate Table
  • Drop Table
  • Insert Into
  • Insert Into select
  • Select * into
  • Select
  • Select Distinct
  • Where
  • And, Or, Not
  • Order By
  • Select Top
  • Like
  • Wildcards
  • In
  • Between
  • Aliases
  • Exists
  • Any, All
  • CASE
  • theory
  • Joins
  • Inner Join
  • Left Join
  • Right Join
  • Full Join
  • cross join
  • cross join excel example
  • understanding common columns
  • finding common columns
  • joining multiple tables
  • Group By
  • Min and Max
  • Count, Avg, Sum
  • group by more than one column
  • Having, where
  • Aggregations with joins
  • Sub queries
  • Correlated Sub queries
  • Non correlated Sub queries
  • theory
  • Unions
  • Union all
  • Intercept
  • Except
  • checking whether both sets or tables are same if A-B is null
  • Creating Views
  • Using Views
  • Creating CTEs
  • Using CTEs
  • Update
  • Delete
  • Sum over partition by
  • Min over partition by
  • Max over partition by
  • Rank over partition by
  • Finding highest value record in each Partition
  • Finding highest n records in each Partition
  • DENSE_RANK, NTILE
  • Constraints
  • creating primary keys, foreign keys
  • Check Constraint
  • Default Constraint
  • Unique Constraint
  • creating constraints, drop constraints
  • theory
  • Functions
  • Function calling another function
  • Table valued function
  • Stored Procedures
  • Stord procedure calling another stored procedure
  • stored procedure calling another function
  • Stored Procedures with default input parameters
  • Stored Procedures with output parameters
  • Python introduction
  • Integer Variables
  • Float Variables
  • Strings
  • Print Formatting with Strings
  • String Operations
  • String Indexing and Slicing
  • String Methods and Properties
  • String Methods
  • String Concatenation and Formatting
  • Tuples and Sets
  • Booleans
  • Key Words in Python
  • Data Types
  • Control flow and loops
  • Python Operators
  • For Loops
  • While Loops
  • Break, Continue and Pass Statements
  • IN and NOT IN
  • NumPy Overview
  • Array Slicing and Indexing
  • Array Manipulation Functions
  • Additional Array Creation Functions
  • Array Arithmetic and Mathematical Functions
  • Pandas Overview
  • Introduction to Series
  • Introduction to Data Frames
  • Selecting Data
  • Data Manipulation
  • Data Aggregation and Grouping
  • Data Cleansing
  • Matplotlib Overview
  • Creating graphs using Matplotlib

...
P Sekhar
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