- 4.7
- 5.0
Official Learning Partner
Course Highlights
This Data Analyst course from SQL School will transform you into a Data Analytics expert. In this Data Analyst course, you will learn the latest analytics tools and techniques, how to work with SQL databases, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment in addition to Mock Interviews, Resume Guidance, Concept wise Interview FAQs and ONE Real-time Project.
Trainer: Mr. Sai Phanindra Tholeti
Profile: https://www.linkedin.com/in/saiphanindra/
Data Analyst Training
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
Data Analyst Training
PLAN A1. T-SQL | Plan B1. T-SQL | Plan C1. T-SQL | |
|---|---|---|---|
| Total Duration | 7 Weeks | 11 Weeks | 14 Weeks |
| Power BI Report Design | ✔ | ✔ | ✔ |
| Power BI Desktop, Custom Visuals | ✔ | ✔ | ✔ |
| Data Modelling with Power Query | ✔ | ✔ | ✔ |
| Data Modelling with DAX | ✔ | ✔ | ✔ |
| Power BI Cloud, Excel Analysis | ✔ | ✔ | ✔ |
| Power BI Mobile, R, REST API | ✔ | ✔ | ✔ |
| PL 300 Exam Guidance | ✔ | ✔ | ✔ |
| Real-Time Project in Power BI | ✔ | ✔ | ✔ |
| SQL Database, T-SQL Queries | ✔ | ✔ | ✖ |
| Tuning Tools, Execution Plans | ✔ | ✔ | ✖ |
| Normal Forms, Joins, Query Tuning | ✔ | ✔ | ✖ |
| Sub Queries, Stored Procedures | ✔ | ✔ | ✖ |
| Excel Pivot Tables, Pivot Charts | ✔ | ✔ | ✖ |
| Python Data Analytics | ✖ | ✔ | ✖ |
| Python DataFrames | ✖ | ✔ | ✖ |
| Pandas & BigData | ✖ | ✔ | ✖ |
| Power Pivot | ✖ | ✖ | ✔ |
| Data Modeling | ✖ | ✖ | ✔ |
| Power Query | ✖ | ✖ | ✔ |
| Data Lookup | ✖ | ✖ | ✔ |
| Total Course Fee ( Payable in Installments) | INR 16000USD 200 | INR 23000USD 290 | INR 28000USD 350 |
SQL Server & T-SQL Schedules
Power BI Training Schedules
Python Training Schedules
SQL SCHOOL
24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.
Technical FAQs
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
- We are Microsoft Partner. ID# 4338151
- ISO Certified Training Center
- Completely dedicated to Microsoft SQL Server
- All trainings delivered by our Certified Trainers only
- One of the few institutes consistently delivering the trainings for more than 8+ Years online as inhouse
- Real-time projects in
- Healthcare
- Banking
- Insurance
- Retail Sales
- Telecom
- ECommerce
I registered for the Demo but did not get any response?
Make sure you provide all the required information. Upon Approval, you should be receiving an email containing the information on how to join for the demo session. Approval process usually takes minutes to few hours. Please do monitor your spam emails also.
Why you need our Contact Number and Full Name for Demo/Training Registration?
This is to make sure we are connected to the authenticated / trusted attendees as we need to share our Bank Details / Other Payment Information once you are happy with our Training Procedure and demo session. Your contact information is maintained completely confidential as per our Privacy Policy. Payment Receipt(s) and Course Completion Certificate(s) would be furnished with the same details.
What is the Training Registration & Confirmation Process?
Upon submitting demo registration form and attending LIVE demo session, we need to receive your email confirmation on joining for the training. Only then, payment details would be sent and slot would be allocated subject to availability of seats. We have the required tools for ensuring interactivity and quality of our services.
Please Note: Slot Confirmation Subject to Availability Of Seats.
Will you provide the Software required for the Training and Practice?
Yes, during the free demo session itself.
How am I assured quality of the services?
We have been providing the Trainings – Online, Video and Classroom for the last EIGHT years – effectively and efficiently for more than 100000 (1 lakh) students and professionals across USA, India, UK, Australia and other countries. We are dedicated to offer realtime and practical project oriented trainings exclusively on SQL Server and related technologies. We do provide 24×7 Lab and Assistance with Job Support – even aftrer the course! To make sure you are gaining confidence on our trainings, participans are requested to attend for a free LIVE demo based on the schedules posted @ Register. Alternatively, participants may request for video demo by mailing us to contact@sqlschool.com Registration process to take place once you are happy with the demo session. Further, payments accepted in installments (via Paypal / Online Banking) to ensure trusted services from SQL School™
YES, We use Enterprise Edition Evaluation Editions (Full Version with complete feature support valid for SIX months) for our trainings. Software and Installation Guidance would be provided for T-SQL, SQL DBA and MSBI / DW courses.
Why Choose SQL School
- 100% Real-Time and Practical
- ISO 9001:2008 Certified
- Concept wise FAQs
- TWO Real-time Case Studies, One Project
- Weekly Mock Interviews
- 24/7 LIVE Server Access
- Realtime Project FAQs
- Course Completion Certificate
- Placement Assistance
- Job Support
- Realtime Project Solution
- MS Certification Guidance
