Data Analyst online training Noida, Best Training Institute for Data Analyst in Delhi NCR

Curriculum:

M S Excel: FEATURES AND FUNCTIONALITY PART 1

Introduction of Excel compare MS Excel 2016 with other Excel versions
Copy/Paste, Paste Special
Add and Edit Comments
Fill Effects
Wrapping text within a cell
Data Formatting
Filter, Advanced Filter, Color Filter
Sorting, Advance Sorting, Custom Sorting
Flash Fill Feature
Text to column functionality of excel to Split words
Absolute, Relative and Mixed Cell References
Protect sheet and workbook
Protect Range
Table Feature
Freeze and unfreeze panes and Split
Excel Keyboard Shortcut Keys
Conditional and Custom formatting

Free Demo

M S Excel: BASIC AND INTERMEDIATE FEATURS AND FUNCTIONALITY PART 2.

Understanding the number format codes
Changing the font color with number format codes
Hide Number and Text based on criteria
GOTO SPEICAL Feature
Creating Name range and Name Manager
Hyperlink from a different sheet, workbook, cell, defined names and websites
Remove Duplicates
Data Validation: Data List, rules, modify error messages
Grouping, ungrouping and Subtotal in Excel

Free Demo

M S Excel: NUMBER FUNCTION

COUNT, COUNTA, COUNTBLANK
COUNTIF
COUNTIF with wildcard
Uses of COUNTIF with real-time example
Unique Entry using the COUNTIF function
Find duplicates using COUNTIF Function
Running Count
Example of COUNTIFS
Example of SUMIFS
Example of AVERAGEIFS
Example of DCOUNT
Example of COUNTA
Example of DSUM
Example of DAVERAGE

M S Excel: LOGICAL AND SUMPRODUCTS FUNCTIONS

Logical Functions: IF, Nested IF, AND, OR, NOT, XOR, IFERROR
SMALL and LARGE function
SUMPRODUCT Function
Use SUMPRODUCT for COUNT
Use SUMPRODUCT for SUM
Use SUMPRODUCT for COUNTIF and COUNTIFS
Use SUMPRODUCT for SUMIF and SUMIFS
Use SUMPRODUCT for AVERAGE and AVERAGEIFS
Use SUMPRODUCT for MAXIF and MAXIFS

M S Excel: TEXT FUNCTIONS IN EXCEL TO SOLVE COMPLEX TEXT PROBLEMS

Introduction of TEXT Functions (LEFT, RIGHT, MID, REPLACE, SUBSTITUTE, etc) available in Excel
Use text functions to Split the words
Use text functions to split characters and numbers What-If Analysis in Excel

M S Excel: DATE AND TIME FUNCTIONS IN EXCEL CREATING DYNAMIC CALENDER FOR WHOLE MONTHS AND YEARS

Introduction of Date Functions available in excel.
Create and Design Calendar using Different Date Functions (WEEKDAY, WEEKNUM, EOMONTH, EDATE) in excel.
Calculate Age using DATEDIF Function
Calculate the date and time difference
count working days using NETWORKDAYS Function

M S Excel: LOOKUP , VLOOKUP , HLOOKUP FUNCTIONS

Introduction of LOOKUP VLOOKUP and HLOOKUP
VLOOKUP with Exact Match
VLOOKUP with Approximate Match
Usage of VLOOKUP Functions using ROW and COLUMN functions
Example of VLOOKUP with Array
Example of HLOOPKUP with multiple Examples
Example of LOOKUP with multiple examples

M S Excel : INDEX AND OFFSET FUNCTION , USES OF ARRAY .

Introduction of the INDEX Function
Introduction of OFFSET Function
Use of INDEX Function
Advance uses of Array Function using INDEX, OFFSET, MATCH, SMALL, LARGE, ROW, and COLUMN function Use of ROW and ROWS function using INDEX and OFFSET function

M S Excel: INDIRECT AND ADDRESS FUNCTION

Introduction of INDIRECT Function
Introduction of ADDRESS Function
Uses of INDIRECT Function
Uses of ADDRESS Function

M S Excel : DATA ANALYSIS USING POWER QUERY AND POWER PIVOT

Creating a Pivot table and Pivot chart in Excel
Adding Slicer and Timeline to analyze in Excel
Using the power pivot to do the Data Analysis
Using Power Query to Source the data from Different Sources

M S Excel : MIS REPORTS AND DASHBOARDS

Introduction of Dashboards and MIS Reports
Adding and Using User Form control in Excel
Recording Macro and run it through a command button
Creating Dynamic Formula based on` User Form control
Creating Dynamic Charts using Formula
Creating 2D charts in Excel
Importance of charts in Dashboards and MIS Reports

M S Excel: CREATING DYNAMIC DASHBOARD ON LIVE DATA

Project work on MIS Dashboard

SQL: INTRODUCTION TO RDBMS AND MICROSOFT SQL SERVER

Introduction to RDBMS concepts
Normalization Technique
SQL Server Architecture
Introduction to Microsoft SQL Server
Introduction to SQL Server Management Studio
Installation of SQL server Management Studio

SQL: CREATING TABLES, DATABASES AND IMPORTING AND EXPORTING DATA

Introduction of Language Statements (DDL, DML, DCL, TCL)
Creating table and DDL commands
Introduction of Import and Export Wizard

SQL : CONSTRAINTS AND DATA TYPES

SQL Data Types
SQL Constraints
SQL Indexing

SQL : SELECT STATEMENT AND WORKING WITH SORTING AND FILTERING DATA

Select Statement
SQL Distinct keyword
SQL Where Clause
SQL wild card concept
SQL Group by and Having clause
SQL CASE statements

SQL : WORKING WITH MULTIPLE TABLES USING JOIN CONCEPT

Introduction of Join
Inner Join
Outer Join
Left Join
Right Join
Self Join
Cross Join
Concept of Nested Join with Where Clause

SQL : USING DML TO MODIFY DATA

SQL Update Statement
SQL Insert Statement
SQL Delete Statement
SQL Transaction control Language

SQL : USING BUILT IN FUNCTIONS

SQL Number Functions
SQL Date Functions
SQL Text Functions
SQL Special Functions

SQL : USING SUBQUERIES CONCEPTS AND TABLE EXPRESSIONS

SQL Scalar Subqueries
SQL Multivalued Sub Queries
SQL Table Values Sub Queries
SQL Common Table Expression

SQL : USING SET OPERATORS AND WINDOWS RANKING, AND AGGREGATE FUNCTIONS

SQL UNION, UNION ALL, INTERSECT AND EXCEPT
SQL CROSS APPLY operator
SQL RANK function
SQL DENSE_RANK function
SQL ROW_NUMBER function
SQL Over Clause

SQL : PROGRAMMING WITH T-SQL AND STORED PROCEDURE

SQL If condition
SQL While Loop
Creating Stored Procedure
Modifying Stored Procedure

SQL :WORKING WITH USER DEFINED FUNCTIONS

Creating User Defined Function
Modifying User Defined Function
SQL Pivot and Unpivot Concept

SQL : APPLYING ERROR HANDLING CONCEPT IN T SQL PROGRAMMING

Implementing T-SQL Error Handling
Redirecting Errors with Try/Catch
Using THROW to pass an error message back to a client
Applying Error Handling in Stored Procedure

SQL : CONCEPT OF CURSOR AND INDEX

Introduction of Cursor
Creating cursor
Modifying cursor
Detailed description about Index

POWER BI : INTRODUCTION TO POWER BI .

Introduction to Visualization
Why Business Intelligence
Introduction to Power BI
Power BI Architecture
Components of Power BI
Power BI Flow
Introduction of Power BI Desktop
Power BI Licensing (Free vs Pro vs Premium)
Power BI Desktop Installation
Power BI Desktop User Interface and Views

POWER BI : DATA LOADING .

Types of Data Sources in Power BI
Data Loading Modes and Advantages

POWER BI: DATA TRANSFORMATION 1.

First Row Header
Duplicate Columns
Split Columns
Remove Duplicate/Columns
Replace Value
Change Data Type
Group BY

POWER BI: DATA TRANSFORMATION 2.

Pivot and Unpivot
Formatting data
Add Custom Columns
Invoke Function
Append Queries
Join Merge Queries
Combine Files (Folder)
Parameters
Other Query Features

POWER BI: DATA MODELING 1.

Components of Data Modeling
Introduction to Data Models
Data Model Engine
Types of Data Model (Flat, Star & Snowflake)
Granularity of Data & multiple fact tables
Data Modeling Relationships
One to One
One to Many
Many to Many

POWER BI: DATA MODELING 2,

Roll Playing Tables
Sorting/Renaming/Hiding Tables
Hierarchy Creation
Formatting & Data Category
Grouping / Binning
Drill Through Reports
What IF Parameter

POWER BI: VISUALIZATION 1.

Designer Options
Power BI Visualization Types
Custom Visualization
Best Practices
Choosing Colors
Types of Charts and Usage
Slicers / Filters
Creating Complete Visualization Report (Practical)

POWER BI: VISUALIZATION 2 .

Continue Creating Complete Visualization Report (Practical)
Story Telling with the created Report
Bookmarks / Selection Pane
Spotlight
Drill Through
Additional Features

POWER BI : SERVICE 1.

Publishing / Deploying Reports
Apps Workspace & Roles
Creating Dashboard
Q&A
Quick Insights
Dashboard Options
Subscription
Alerts

POWER BI: SERVICE 2 .

Export Options (Embed, Web, Power Point…etc.)
Excel Integration
Row Level Security
Data Refresh Concept
Gateway and Installation
Power BI Mobile Service
Power BI Admins Roles
Audit Logs

POWER BI: DAX 1.

Introduction DAX
DAX Data Types
Calculated Columns
Calculated Tables
Calculated Measures
Calculated Columns vs Measures
Aggregated Functions (SUM, MIN, MAX, AVG, COUNT)
Relate Functions (RELATED & RELATED TABLE)
Iterative Functions (SUMX, AVGX, COUNTX)
Variables (VAR)
Logical functions (AND, OR, IF, SWITCH)
Table Functions (VALUES, FILTER, CALCUILATETABLE)
FORMAT FUNCTION, FIND, SEARCH, SUBSTITUE, VALUE, UNION, ROW, ADDCOLUMNS, SUMMARIZE
Handling Blanks (ISBLANK, NOTISBLANK)
Rank Functions (RANKX)

POWER BI: DAX DATE AND TIME INTELLIGENCE.

CALCULATE (ALL, ALLEXCEPT, ALLSELECTED)
Understand Row & Table level Filter Context
Date Functions (DATEADD, DATEDIFF, TODAY Required Date Formats)
Calendar Functions (CALENDAR, CALENDAT AUTO)
Time Intelligence functions (TOTALMTD, TOTALQTD, TOTALYTD, PARALLELPERIOD, SAMEPERIODLASTYEAR, PARALLELPERIOD, RUNING TOTAL)
SEMI ADDITIVE (OPENING BALANCE, CLOSING BALANCE, LAST DATE, FIRST DATE, LASTNONBLANK, FIRSTNONBLANK)

POWER BI: PROJECT & DISCUSSION(Q & A).

Project 1
Project 2

PYTHON: INTRODUCTION .

Introduction to Programing Language
Introduction to Python
History of Python
Why Python and Comparison with all languages
Version of Python
Environment Setup

Discussed about IDE
In window
Mac

PYTHON : STARTING WITH VARIABLES , COMMENTS

Variables
Comments
Data Types in Python

Numbers
String
List
Tuple
Dictionary

PYTHON : OPERATOR AND I/O FUNCTIONS.

Operators

I/O Functions
Type Conversion

PYTHON : IF CONDITION AND DECISION MAKNG .

Basic Introduction
If, If else, Nested if and elif

PYTHON : LOOP CONCEPT.

Loops
Basic Introduction
Need of Loop
While Loop
For Loop

PYTHON : FUNCTIONS.

Introduction
Pre Define Functions
User Define Functions
Lambda Function

PYTHON : DEEP DIVE IN DATA TYPES OR DATA STRUCTURE .

String
List
Tuple
Dictionary

PYTHON: DEBUGGINGH AND ERROR HANDELING .

Section introduction
Raising our own error
Try and Except Block
Try, Except, Else and Finally
Debugging with PDB

PYTHON : MAKE HTTP REQUEST .

TTP Introduction
HTTP verbs and API
Writing your First Python Request
Requesting Json with Python
Sending Request with Params
API Projects

PYTHON : OBJECT ORIENTED PROGRAMMING .

Section Introduction
Defining Class and Objects
Abstraction and Encapsulation
Creating Class and Instances
INIT Method

PYTHON : OOPS EXERCISE .

Introducing the class Attributes
Class Methods
Inheritance and Objectives
All about the Properties
Introduction to Super
Polymorphism Introduction
Some Special Methods

PYTHON: ITERATORS AND GENERATORS .

Section Introduction
Iterators vs Iterables
Writing own Custom iterators
Writing our own Version of Loops
Making a Deck Class Iterable
Testing Memory Usage with Generators
Generator Expression and Speed Testing

PYTHON : DECORATORS .

Higher Order Functions
Introduction to Decorators
Decorators with Different Signature
Using Wraps to preserver Metadata
Building a Speed Test Decorator

PYTHON : TESTING .

Section Introduction
Why Test
Assertions
Introduction to Doctest
Introduction to Unit Test
Hands on work on Testing

PYTHON: FILE INPUT AND OUTPUT .

Section Introduction
Reading the Text File: Open, read and Write
Reading the File: Seek and Cursor
The with Statement
Writing to Text File
Working on Csv and Pickling
Reading CSV File
Writing CSV File

PYTHON : WEB SCRAPING WITH BEAUTIFUL SOUP .

Introduction to Web Scraping
Is Scraping ok?
Selecting with Beautiful Soup
Navigate with Beautiful Soup
Web Scraping Projects

PYTHON: REGULAR EXPRESSION

Introduction to Regular Expression
Writing basic Regix
Regix basic Quantifiers

PYTHON: PYTHON + SQL.

Introduction to the section
Installing Mysql
Why Mysql
Sql Basic: DDl , DML
Inserting with Python
Fetching the Data in Python from MySQL

PYTHON: TAKE AWAY FROM THE TRAINING .

There will be Assignment on Each and Every Section
Hands-on experience on Each and Every Section
Interview Questions will also be discussed
By this Content you can get a Job in Python Language
Project 1
Project 2

Course Highlights

No. of hours: 100 Hours

Star Rating: (16)

Trainer:

Devbrat Tripathi

Mr. Devbrat Tripathi has worked with corporate industry for almost 10 years and associated with reputed companies like UHG, BOA, AON and Microsoft. His highest qualification is MCA from PTU- Jalandhar, India.

Fee:

Online Virtual Class Room

Enroll in any above batch and attend live class at scheduled time

28320

Upcoming Batches:

2024-10-19 10:00 AM IST	Weekend Batch (2 Hours Sat & Sun)	₹28320 ₹22656 (20% OFF) Offer Ends in 10 d: 12h : : 51s
2024-10-07 8:00 AM IST	Weekdays Batch (1 Hour Mon - Fri)	28320
2024-10-14 8:00 PM IST	Weekdays Batch (1 Hour Mon - Fri)	₹28320 ₹22656 (20% OFF) Offer Ends in 5 d: 12h : : 51s

FAQ:

1. Where we can use the data analyst concept?

We can use this concept anywhere in any company whether it is a small company or big company. but mostly it is used for the collection of big data .

2.Any Prerequisite to learn Python?

There is no prerequisite to learn Data Analyst in noida. If you are familiar with computers or have a basic concept of any other programming language it would be an added advantage to you. By the way, we will start this training from scratch.

3. Recommend Audience for Data Analyst course in Noida:

Anyone interested in learning Data Analysis can join this course like students and working professionals.

4. In case of my absence, how can I manage my class?

You will get access to LMS (Learning Management System), if you missed your class you can refer to the recorded session in your LMS. If you have any doubts you can ask in your next class whenever you join

5. How much time it will take to complete ?

It will take 100 hrs. to complete this training program

6. Who is the Instructor?

Our instructors are industry experts having more than 10 years of corporate experience. Since they have rich experience in their domain they will train as per the industry standards.

7. Will you help us in Job placement?

We have tied up with more than 100+ companies in corporate industry. We will schedule your interview after successful completion of our course.

8. Will you help us in resume creation?

Yes, we will help you create your resume so that it can be shortlisted easily for an interview.

9. Will you help us to get the software?

Yes, we will help you with the Trial version of the software

10. How long can I access my (LMS) learning management System?

Once you enroll for the course, you can access the LMS for life long.

11. How can I get the certification?

Once you will complete your course, you will appear for an online test. Based on your score we will issue the certificate.

12. What is a Self-paced course?

If you enroll for a self-paced course you can access the pre-recorded sessions and you can do self-learning. You can complete your course as per your availability.

13. What is an instructor-driven course?

This is online virtual classroom training, since this is a live class, you can clear your doubts in the class.

14. What if I have more queries or concerns?

You can write an email at info@wifilearning.com or you can contact us at our Office numbers at 91-9999468661.

15. How can I start a career in data analytics?

To start a career in data analytics, consider acquiring relevant skills in statistics, programming, and data visualization. Completing courses, certifications, or obtaining a degree in data analytics can also be beneficial. Networking and gaining practical experience through projects are valuable steps as well. Wifi learning can help you with that for an inquiry call now.