Data Analyst Online Training

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This Data Analyst master course from SQL School will transform you into a Data Analytics expert. In this course, you will learn SQL, Power BI, Python Anaytics and Excel Integrations with End to End Project Work for your resume, job requirement. This best Data Analyst Training program also includes Mock Interviews, Resume Guidance, Concept wise FAQs and more .. ! Register Now

Trainer: Mr. Sai Phanindra Tholeti
Profile: www.linkedin.com/in/saiphanindra/

Duration : 11 Weeks Fee : 24k, payable in installments

Data Analyst Training

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Module 1 : SQL Server & T-SQL Queries

Ch 1: DATABASE INTRODUCTION

Databases Introduction & Purpose
Database Types : OLTP, DWH, OLAP
Microsoft SQL Server Advantages, Use
SQL Server Components and Usage
Microsoft SQL Server – Career Options
Developer, DBA, Data Engineer
Data Analyst, Data Scientist Careers
SQL : Purpose, Real-time Usage Options
SQL Versus Microsoft T-SQL [MSSQL]
Course Plan, Real-time Project, Resume
24 x 7 Online Lab for Remote DB Access
Versions and Editions of SQL Server
SQL Server Pre-requisites : S/W, H/W
System Configuration Checker Tool

Ch 2: SQL SERVER INSTALLATION

SQL Server & SSMS Installation Plan
SQL Server Pre-requisites : S/W, H/W
SQL Server 2022 & 2019 Installation
Database Engine Feature, OLTP
Instances : Types and Properties
Default Instance, Named Instances
Service and Service Account Use
Authentication Modes and Logins
Windows Logins and SQL Logins
SQL Server Management Studio
Server Connections with SSMS Tool
Local and Remote Connections
System Databases: Master and Model
MSDB, TempDB, Resource Databases

Ch 3: SSMS Tool, SQL BASICS – 1

Creating Databases: Files [MDF, LDF]
Creating Tables in User Interface
Data Insertion & Report in User Interface
SQL : Purpose and Real-time Usage
SQL Versus T-SQL : Basic Differences
DDL, DML, SELECT, DCL and TCL
Creating SSMS Sessions : SPID
Create, Connect Databases using SQL
Creating Tables with INT, CHAR
Data Storage, Inserts – Basic Level
Table Data Verifications with Select
SELECT Statement for Table Retrieval
Identify Databases and Tables
Identify Sessions and Session ID

Ch 4: SQL BASICS – 2

Creating Tables: VARCHAR, FLOAT
Single Row Inserts, Multi Row Inserts
Rules for Data Insertion Statements
SELECT with WHERE Conditions
AND and OR Operators Usage
IN Operator and NOT IN Operator
Between, Not Between Operators
LIKE and NOT LIKE Operators
ORDER BY, TOP & OFFSET
Basic Sub Queries with SELECT
UPDATE Statement & Conditions
DELETE & TRUNCATE Statements
ALTER, ADD COLUMN Statements
DROP Statements: Table, Database

Ch 5: SQL Basics – 3, TSQL INTRO

Database Objects : Tables and Schemas
Schemas : Group Tables in Database
Schemas : Security Management Object
Creating Schemas & Batch Concept
Using Schemas for Table Creation
Data Storage in Tables with Schemas
Data Retrieval & Usage with Schemas
Table Migrations across Schemas
Import and Export Wizard in SSMS
Data Imports with Excel File Data
Performing Bulk Operations in SSMS
Temporary Tables : Real-time Use
Local and Global Temporary Tables
# and ## Prefix, Scope of Usage

Ch 6: Constraints, Index Basics

Constraints and Keys – Data Integrity
NULL, NOT NULL Property on Tables
UNIQUE KEY Constraints: Importance
PRIMARY KEY Constraint: Importance
FOREIGN KEY Constraint: Importance
REFERENCES, CHECK & DEFAULT
Candidate Keys and Identity Property
Database Diagrams and ER Models
Relationships Verification and Links
Indexes : Basic Types and Creation
Index Sorting and Search Advantages
Clustered and NonClustered Indexes
Primary Key and Unique Key Indexes
Need for Indexes – working with Keys

Ch 7: Joins Basics, TSQL Queries

JOINS – Table Comparisons Queries
INNER JOINS For Matching Data
OUTER JOINS For (non) Match Data
Join Queries with “ON” Conditions
Left Outer Joins – Example Queries
Right Outer Joins – Example Queries
FULL Outer Joins: Realtime Scenarios
CROSS JOIN and CROSS APPLY
One-way, Two way Data Comparisons
Using Table Aliases & Column Aliases
Optimizing Join Queries with Indexes
Choosing Correct Comparison Columns
Joining Unrelated Tables in TSQL
Self References, Self Joins in TSQL

Ch 8: Group By, Views & Excel

GROUP BY: Importance, Realtime Use
GROUP BY Queries and Aggregations
Group By Queries with Having Clause
Group By Queries with Where Clause
Using WHERE and HAVING in T-SQL
Group By with Joins in TSQL
Query Execution Order & Aliases
Joins with Sub Queries, Formatting
Database Objects: Overview & Usage
Views: Types, Usage in Real-time
Creating, Executing & Verifying Views
Storing Queries in Database Views
Excel Analytics – Joins & Views
Excel Office Data Connection Reports

Ch 9: Functions, Procedures Basics

Functions with SQL Server, TSQL
Scalar, Inline, Table Functions
Variables: Declare, Real-time Use
Creating, Executing Functions
Functions for Computations
Functions for Parameterized Joins
Procedures: Usage in Real-time
Using Parameters in SQL Server
Parameterized Joins in TSQL
Compilation with Stored Procedures
sp_help, sp_helptext, sp_helpindex
sp_helpdb, sp_rename, sp_recompile
System Views For Metadata Audits
DBID, DBName, ObjectID, ObjectName

Ch 10: TRIGGERS & TRANSACTIONS

Triggers – Purpose, Real-world Usage
FOR/AFTER Triggers – Real time Use
INSTEAD OF Triggers – Real time Use
INSERTED, DELETED Memory Tables
Using Triggers for Data Replication
Enable Triggers and Disable Triggers
Database Level, Server Level Triggers
Transactions : Types, ACID Properties
Transaction Types and AutoCommit
EXPLICIT & IMPLICIT Transactions
COMMIT and ROLLBACK Statements
Batch Concept and Go Statement
Open Transactions in Real-time
Using Conditional Commits, Rollbacks

Ch 11: Normal Forms, Cursors

First Normal Form and Atomicity
Third Normal Form and MVD Property
Boycee-Codd Normal Form : BNCF
Fourth Normal Form : Advantages
Self Reference Keys and 4 NF Usage
1:1, 1:M, M:1, M:M Relationship Types
Computed Columns, Variant Type
Linked Servers, Remote Joins in TSQL
2 Part, 3 Part, 4 Part Naming Styles
Remote Joins Queries and Aliases
Cursors – Basics, Data Operations
Cursors – Life Cycle & Declaration
Cursors Types, FETCH Operations
Cursors – Deallocate, Real-world Use

Ch 12: TSQL Merge, Cursors

IIF() Function with SELECT Query
WHEN..THEN..ELSE
WHEN MATCHED, NOT MATCHED
Incremental Loads, Upsert Statement
Stored Procedures: Merge Statement
UNION and UNION ALL Operator
Window Functions: Rank, Dense Rank
Row_Number, PartitionBy in TSQL
Duplicate Row Identification, Deletion
Grouping, Cube, Rollup, Lag, Lead
Data Types: Numerical, Date, Time
Data Types: Characters, Real, Float
Date & Time Functions, DateAdd
String Functions, Concat, SubString

Case Study 1: Database Design with Tables,
Constraints, Keys & Relations

Case Study 2: Joins with Group By,
Sub Queries, Views, Excel Analytics

Module 2 : Power BI

Part 1: Power BI Report Design

Ch 1: POWER BI INTRODUCTION

Power BI : Introduction to Analytics
Power BI Tools Suite, Advantages
Power BI : Career Options, Plan
Power BI Developer Job Role
Microsoft Data Analyst Job Role
Big Data Analyst Job Role
Power BI Data Analyst (PL 300)
Data Engineer*, Power BI (DP 500 *)
Artificial Intelligence (AI) Visuals
AI Enabled Power BI Features
Course – Lab Plan with Design Tools
Need for Power Query & DAX
Power BI Licensing Types
Power BI Cloud – Advantages
Power BI Report Server Advantages

Ch 2: Basic Report Design

Power BI Eco System: Architecture
Data Sources & Types in Real-world
Report Types: Interactive, Paginated
Analytical Reports & Mobile Reports
Data Sources : File, Database, Web
Visualizations : Report Shapes
Power BI Design Tools, Requirements
Power BI Desktop Tool : Installation
Desktop Interface: Overview, Canvas
Get Data, Data View, Report View
In-Memory Xvelocity Database
Basic Visuals: Table, Tree Map
Data Labels, Legend, Category
Local Store: PBIX & PBIT Files
Data Points and Tooltips

Ch 3: Visual Interaction, Visual Sync

Visual Interaction with Data Points
Disabling / Enabling Interactions
Edit Interactions: Format Options
Spotlight and Focus Mode
Report Export to CSV, PDF
Tooltip Options and Usage
Working with Pages in PBI
Rename, Duplicate, Hide Pages
Slicer Visual : Real-time Usage
Orientation, Selection Properties
Slicer Settings : Tiles & Slider
Single & Multi Select, Header
Number, Text, Show Summary
Date Slicer and Value Selections
Slicer List, Dropdowns & Clear

Ch 4: Grouping & Hierarchies

Grouping : Visuals with Pdf Sources
List Grouping and Binning Options
Grouping Static / Fixed Data Values
Grouping Dynamic / Changing Data
Bin Size and Bin Limits (Max, Min)
Bin Count and Grouping Options
Group with Bins & Clustering
Group, Layer with Selection Pane
Creating Hierarchies in Power BI
Independent, Dependant Drill-Down
Drill-Down with Interactive Reports
Conditional Drilldowns, Data Points
Drill Up Buttons and Operations
Expand & Show Next Level
Dynamic Data Drills Limitations

Ch 5: Filters & Bookmarks

Filters : Types and Usage in Real-time
Visual Filter, Page Filter, Report Filter
Basic, Advanced and TOP N Filters
Category and Summary Level Filters
Data / Drill Options, DrillThru Filters
Keep All Filters” Options in DrillThru
CrossReport Filters, Include, Exclude
Drill-thru Filters, Page Navigations
Bookmarks : Report Navigations
Buttons, Images with Actions
Selection Pane, Actions, Text URLs
Show Data and See Records
Custom Tooltips, Table Visual
Table Vs Matrix : Drill-downs
Styles, Cell Properties, Databars
Conditional Formatting, Divergent

Ch 6: Big Data Access, Visuals

OLTP Databases, Big Data Sources
Azure Database Access, Reports
Import, Direct Query & Dual Mode
Data Modeling: Do Not Summarize
Data Modeling: Currency, Relations
Power BI Archtiecture, Eco System
Power BI Interface for Reports
Stacked Chart, Clustered Chart
Line Chart, Area Chart, Bar Chart
100% Stacked Bar & Column Chart
Map Visuals: Tree, Filled, Bubble
Small Multiples, Legends, Axis
Cards, Funnel, Table, Matrix
Scatter Chart : Play Axis, Labels
Waterfall Chart, Multi Row Cards

Part 2: Power Query, Cloud (Service)

Ch 7: POWER QUERY LEVEL 1

Power Query M Language Purpose
Power Query Architecture and ETL
Data Types, Literals and Values
Power Query Transformation Types
Table & Column Transformations
Text & Number Transformations
Date, Time and Structured Data
let, source, in statements @ M Lang
Get Data, Table Creations and Edit
ETL Operations with Power Query
Merge Transformations in Power BI
Join Kinds: Inner, Outer & Apply
Union All Transformation & Appends
Power Query Editor, Step Edits
Close & Apply Options. Report Design

Ch 8: POWER QUERY LEVEL 2

Query Duplicate, Query Reference
Group By and Advanced Options
Aggregations with Power Query
Transpose, Header Promotion
Reverse Rows and Row Count
Data Type Changes & Detection
Replace Columns: Text, NonText
Advanced Query Edit Options
Replace Nulls: Fill Up, Fill Down
Pivot, Unpivot Transformations
Move Column and Split Column
Date & Time Transformations
Derive Year, Quarter, Month, Day
Add Column : Query Expressions
Query Step Inserts and Step Edits

Ch 9: POWER QUERY LEVEL 3

Big Data Loads : Parameter Queries
Creating Parameters in Power Query
Parameter Data Types, Default Lists
Static & Dynamic Lists: List Queries
Convert Tables to Lists, Use Cases
Linking Parameters to Queries
Testing Parameters with Canvas
Multi-Valued Parameter Lists
Creating Lists in Power Query
Converting Lists to Table Data
Invoke Function, Type Conversions
Function Query & Parameter List
Columns From Examples, Indexes
Conditional Columns, Expressions
Disable / Enable Data Loads

Ch 10: POWER BI CLOUD – 1

Power BI Cloud Components
App Workspaces, Report Publish
Reports & Related Datasets Cloud
Creating New Reports in Cloud
Report Publish, Report Uploads
Report Edits and New Reports
Report Actions: Downloads
Dataset Usage Options in Cloud
Dashboards Creation and Usage
Pining Visuals and Report Pages
Visual Pin Actions in Dashboards
Dashboard & LIVE Interactions
Media Tiles: Images, Custom Links
Q & A Option with Dashboards
Pin with Q & A; Standard Visuals

Ch 11: POWER BI CLOUD – 2

Report Actions : Share, Subscribe
Report Actions : Lineage, Embed
Report Actions : Export Options
Report Actions : Public User Access
Dashboard Actions : Share, Subscribe
Dashboard Actions : Themes, Lineage
Dashboard Actions : Share, Subscribe
Favorite, Insights, Embed Code
Gateways Configuration, PBI Service
Gateway Types, Cloud Connections
Gateway Cluster, Add Data Sources
Data Refresh : Manual, Scheduled
Power Query Parameters, Gateways
DataFlows, Power Query in Cloud
Lineage, Share, Subscribe, Insights
Performance Inspector& Gateways

Ch 12: POWER BI CLOUD – 3

Workbooks : Excel Online & Pins
Power BI Apps: Creation & Usage
Power BI Segments, Content
Navigation Screens, Audience
App Publish, Verification & Edits
Export, Share & Subscribe
List View & Lineage View Options
Power BI Scorecards: Realtime Use
Paginated Reports – Design & Usage
Power BI Report Builder Tool
Microsoft Report Builder Tool
Report Builder : Datasets, Charts
Report Builder : Bar Charts, Fields
Report Builder : Creating RDL Files
Paginated Reports : Deployments

Part 3: DAX & Report Server

Ch 13: DAX Functions – Level 1

DAX : Importance in Real-time
DAX Data Types, Syntax Rules
DAX Measures and Columns
ROW Context and Filter Context
Operators, Special Characters
DAX Functions, Vertipaq Engine
DAX Cheat Sheet : Expressions
Data Analytics with DAX
DAX Measures : Expressions
ISBLANK, IF, IN, SUM
SUMX, AVG, AVERAGEX
Data Models: Fact, Dimensions
Detecting Relations for DAX
Star & Snowflake Schemas
Data Modeling Options in DAX

Ch 14: DAX Functions – Level 2

Quick Measures in Power BI
Average and Filtered Average
Running Totals, EARLIER( )
RELATED, COUNTROWS
CALCULATE Function Conditions
ALL Members Scope & IN
Account and Time Calculations
Star Rating, DAX Expressions
Data Modeling Options in DAX
1:1, 1:M and M:1 Relations
Working with Facts & Measures
Modeling : Missing Relations
Relationships & Importance
Modeling : Relation Management
Modeling with Multiple Keys

Ch 15: DAX Functions – Level 3

DAX : Variables and Expressions
Dynamic Expressions, RETURN
Current Value, Previous Value
SELECTED VALUE, Joins
FORMAT Function with DAX
RELATED, Joins in DAX
DAX Expressions with SQL DB
Time Intelligence Functions
Date Dimension : Generation
CALENDAR(), DATESYTD()
TOTALYTD, TOTALQTD
TODAY, DATE, DAY with DAX
SELECTEDVALUE, FORMAT
Date, Time and Text Functions

Ch 16: DAX Functions – Level 4

RLS: Row Level Security
Data Models in Power BI Desktop
DAX Roles Creation and Testing
DAX Expressions & Operators
PBIX Uploads: Power BI Cloud
Dataset Security with DAX Roles
Entity Sets and Slicing in DAX
Dataflows with Power BI
Analytical Reports – DAX Usage
Creating Data Models with DAX
Datasets in Excel and Dashboards
Using Excel Analyzer in Power BI
Power BI Data Source in Excel
Connection Strings and Refresh
Analytical Reports – Limitations

Ch 17: Power BI Report Server

Power BI Report Server Config
SQL Server Instance Verifications
Report Server DB, Temp Database
WebService & WebPortal URL
Uploading Interactive Reports
End User Report Share (pdf)
Power BI Desktop RS Tool
Interactive Reports: Report Server
Mobile Reports : Design Options
Mobile Reports : Grids, Elements
Mobile Reports : Uploads, Edits
Paginated Reports : Deployments
Paginated Vs Interactive Reports
Paginated Vs Analytical Reports
Paginated Vs Mobile Reports
Power BI Report Server Vs Cloud

Ch 18: Power BI Admin & AI

Power BI Cloud Management
Power BI Admin : Alerts
Workspace Management, Users
Security: Report, Dataset Levels
Security: Dataset, App Levels
Security: Workspace Options
PBI Performance Inspector
Power BI & Artificial Intelligence
Power BI & CoPilot Add-Ins
AI Visuals & Big Data Analytics
Smart Narrative and Q & A
Infographics, Icons and Labels
Key Influencer Visual in Power BI
Metrics Visual, Performance
Paginated Reports Visual

Power BI : Realtime Project (Sales – Retail)

Phase 1 : Basic Report Design

Project Requirement Analysis
Requirement Gathering, FSA
Report Design with Excel
Basic Data Modelling
Infographics, Histograms
Analytics and Formating

Phase 2 : SME Level

Report Design with SQL DB
SQL Database : Joins, Views
Dual Storage Mode, SQL Queries
Data Modeling, Power Query
Dynamic Connections, Azure DB
Parameters and M Lang Scripts

Phase 3: Deployments (Cloud, Server)

DAX Requriements, Analysis
Cloud and Report Server
Custom Visualizations
3party Visuals & REST API *
Project FAQs and Solutions
One – One Resume, Mock Interview

Module 3 : Python

Part 1: Python Fundamentals

Ch 1: Data Analytics Intro & Python

Data and Databases : Introductions
Data Analytics Job Role
Python : Introduction & Advantages
Python : Career Options, Scope
Python for Big Data Analytics
Why Python? Usage Options
Python Installation : Multi OS
Anaconda Software Installation
Jupyter Interface for Python
Python Activities with Jupyter
Notebooks : Python Web Interface
Notebooks and Cells: Introduction

Ch 2: Basic Operations with Python

Python Interface : Creating Notebook
Adding Cells, Saving Notebook
Executing Basic Cells; Result Window
Single Line & Multi Line Comments
Save, Open / Clone Notebooks
Indentation Options with Python
Python : Internal Architecture
Code Editor, Source Files
Compiler, Byte Code, Virtual Machine
Program Execution : Py, PYC and PVM
Python Libraries / Modules
Compiler Versus Interpreter

Ch 3: Data Types & Variables

Integer / Int Data Types
Float & String Data Types
Boolean Data Types, Binary Types
Sequence Types: List, Tuple
Range, Complex & memoryview
Retrieving Data Type: type()
Python Variables: Naming
Camel / Pascal / Snake Case
Multi Assignments & Casting
Multi Word Variables, PRINT
Multiple Variables and Vales
Unpack Collection, Outputs

Ch 4: Python Operators, Conditions

Python Operators : Arithmetic
Assignment, Compare Operators
Logical, Identity Operators
Member & Bitwise Operators
Operator Precedence Options
Python Operator Expressions
Python If … Else Statement
Short Hand If Statement, Use
OR, AND and NOT Statements
Pass Statement with Python
ELIF and ELSE IF Statements
Ternary Operators in Python

Ch 5: Python Loops, Iterations

Python Loop & Realtime Use
Python While Loop Statement
Break and Continue Statement
Using Print with While()
Iterations & Conditions
Exit Conditions : Cautions
Python For Loop Statement
Break, Continue & Range
Python Iterators : Creation
__iter__() and __next__()
Iterator vs Iterable
iter() and Looping Options

Ch 6: Python Collections

Python Collections (Arrays)
Python Collection Data Types
List, Tuple, Set, Dictionary
List Items, Ordered & Length
list() Constructor, print()
Python Tuples, Tuple Items
tuple() Constructor, Usage
Python Sets : Syntax Rules
Duplicates, Types, Ordered
Python Dictionaries: Usage
Changeable, Ordered Data
Dictionary Construct, type()

Part 2: Python For Data Analytics – 1

Ch 7: Python Functions

Python Functions : Realtime Use
Function : Creation, Execution Call
Function Parameters, Arguments
Arguments Number, Arg keyword
Arbitrary Keyword & **kwargss
Default & List Value Parameters
Python Lambda Functions
Using Lamdba Options in Python
Anonymous Functions in Python
Arguments, Expressions
Recursive Functions, Usage
Return & Print with Lamdba

Ch 8: Python Classes & Arrays

Python Classes & Objects
Python Classes : Usage
__init__() Function
__str__() Function
Self Parameters & Usage
Object Properties Options
Python Inheritance & Classes
Adding Parent & Child Classes
Add __init__() Function
Using super() Function
Add Properties, Methods
Polymorphism in Python

Ch 9: Python Modules

Python Modules : Creation
Import Python Modules
Using Variables in Modules
Naming, Renaming Module
Built In Modules & dir
Using Modules, Properties
datetime module in Python
Date Objections, strftime Method
import datetime, datetime.now()
Using Python Constructors
Conditional Columns, Expressions
Disable / Enable Data Loads

Ch 10: Python JSON & RegEx

Python JSON Concepts, Usage
Python Dictionary & import json
Convert from Python to JSON
Python Objects into JSON strings
Result Formatting & Ordering
json.dumps, print options
Python Regular Expressions
RegEx Module in Python
RegEx Functions : findall
search() Function & split
span() function & Usage
Using RegEx with JSON

Ch 11: Python User Inputs & TRY

Python Try Except
Python Exception Handling
NameError Resolution
Python Finally Block, Usage
Raise an exception method
TypeError, Scripting in Python
Python User Inputs
Python String Formatting
Multiple Values & String
Python Index Numbers
Named Indexes, Usage
input() & raw_input()

Ch 12: Python File Handling

File Handling
r, a, w, x modes
t, b Operations
File Activities
Read Only Parts
Loop, Close Files
Python File Write
Appending, Overwriting
Create a New File
import os, path.exists
f.open, f.write
f.read, f.close

Part 3: Python For Data Analytics – 2

Ch 13: Data Analytics – Pandas

Python Modules & Pandas
Why Use Pandas?
Pandas Codebase & Usage
Installation of Pandas
import & pandas.DataFrame
Checking Pandas Version
Pandas Series
one-dimensional array
Labels : Creation, Use
series(), print()
Pandas DataFrames
Dataframes & Series

Ch 14: Data Analytics – DataFrames

Pandas DataFrames in Python
DataFrame() & Realtime Usage
Indexes & Named Options
Locate Row and Load Rows
Row Index & Index Lists
Load Files Into a DataFrame
Pandas Read CSV
pd.read_csv() Function
pd.options.display.max_rows
df.to_string() Function
Dictionary as JSON
tail() & null() Function

Ch 15: Data Analytics – Pandas

Pandas – Cleaning Data
Removing Rows, Data Cleansing
Replace, Transform Columns
Data Discovery & Column Fill
Identify & Remove Duplicates
dropna(), fillna() Functions
Pandas – Data Correlations
Data Relations and Validations
Good & Bad Correlation
Perfect Correlation Scenarios
Python Data Plotting Options
matlib Module & Plotting

Ch 16: SQL Server with Python – 1

Installing SQL Server DB Engine
Install Machine Learning Services
SQL Server Management Studio
Install Azure Data Studio Tool
sp_execute_external_script
Input Data & Result Sets
DDL & DML with Python
SQL_out, SQL_in with Python
Variables & Parameters in Python
Python Version, Package List
Script Parameters & Usage
WITH RESULT SETS Options

Ch 17: SQL Server with Python – 2

Using pandas.Series with SQL Server
Indexing Methods and Realtime Use
Convert series to data frame
DataFrames with SQL Server
Output values into data.frame
Output Datasets and Usage
pymssql package in SQL Server
pip list & Package Manager
Python runtime, Py Package Index
pymssql.connect & Usage
Query Execution & Result
Cursor Variables & Usage

Ch 18: Power BI with Python

Installing Power BI Desktop
Using Python Script Visual
PyScript Options & Tuning
Settings, Labelling Options
Running and Testing Scripts
Data Validations in Power BI
Power BI Cloud : ipynb Scripts
Python in Desktop Vs Cloud
Interactive Reports with Python
Power Query Options (M Lang)
Data Formatting with Python
Integrate SQL, Power BI, Python

SQL Server & T-SQL Schedules

S No	Time (IST, Mon - Fri)	Start Date	Trainer	Register
4	8 PM - 10 AM	Dec 2nd	Mr. Sai Phanindra	Register
2	9 AM - 10 AM	Nov 25th	Mr. Sai Phanindra	Register
3	10:30 AM - 11:30 AM	Dec 10th	Mr. Sai Phanindra	Register
1	6 AM - 7 AM	Dec 16th	Mr. Sai Phanindra	Register

Power BI Training Schedules

S No	Time (IST, Mon - Fri)	Start Date	Trainer	Register
1	8 AM - 9 AM	Nov 20th (Started)	Mr. Sai Phanindra	Register
2	7 PM - 8 PM	Dec 10th	Mr. Sai Phanindra	Register

Python Training Schedules

S No	Time (IST, Mon - Fri)	Start Date	Register
1	7 AM -8 AM	Dec 3rd	Register
2	8 PM - 9 PM	Nov 26th	Register

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Who is SQL School? How far you have been in the training services ?

SQL School is a registered training institute, established in February 2008 at Hyderabad, India. We offer Real-time trainings and projects including Job Support exclusively on Microsoft SQL Server, T-SQL, SQL Server DBA and MSBI (SSIS, SSAS, SSRS) Courses. All our training services are completely practical and real-time.CREDITS of SQL School Training Center

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