Data Analyst

Diploma in Data Analyst

Data Analyst is Most demanded in company. Data analytics help a business optimize its performance, perform more efficiently, maximize profit, or make more strategically-guided decisions. The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption

9+ Expert Mentors

200+ Assignments

Average CTC 9 LPA

( 755 Review)

: 6 Months or 120 Hours

: Beginner to Advance

: Practical Learning

Talk to Program Advisor

2415 Enrolled

You will Learn

Variable

Course Key Points

Data types

Operators

Functions

Flow control

Python files

Create Database

Aggregate Function

Pivot Table

Update & Delete

Clauses

Statements

Slicer

Power Query

Constraints

Features

Installment

Digital
Notes

Flexible Timing

Live Projects

Job
Assistance

Smart
Classes

Expert
Trainers

Practical
Learning

Course Content

Module 1 : Advance Excel (Official and Financial) with MIS Reporting & A.I

Functions and Formula (Logical, Reference, Text, Math, Finance etc)
(HLOOKUP, VLOOKUP, match, trim, date, time, if, sumsq, daverage, len, ifna, FV etc)
Structure Build, Reference, Range,
MIS Reporting
Practical Illustration and Projects with Groups of Function / formula
Menu / Tabs (Pivot Table, sorting, filtering, grouping, consolidate, scenario, goal seek, Data table, data validation, conditional formatting etc)

Module 2: Power BI

Introduction to business intelligence (BI), Stages of business intelligence (BI), Use cases of BI, Various BI tools, Overview of data warehouse and concepts, Introduction to Power BI, Why Power BI?, Power BI components, Power BI pricing structure, Building blocks of Power BI, Architecture of Power BI, Introduction to Power BI desktop, Installation of Power BI desktop, The key features of Power BI workflow, Process of creating reports in Power BI, Creating Dashboard, Using DAX, Power Query, Different types of Charts. Etc

Module 3: Structured Query Language (SQL)

Introduction to SQL, Setting the Environment, About MySQL, what is database? Types of databases, DBMS (Database management System), Creating Database, Drop Database, Select Database, Tables in SQL, Datatypes, Constraints, SQL Operators, SQL Queries, SQL Commands (DDL, DML etc) SQL Clauses, Aggregate Functions, Joins, Views etc.

Module 4: Python

Introduction to Python, Python Modules, Operators, Conditional Statements, Loop Statements, Strings, List Collection, Tuple Collection, Set Collection, Dictionary Collection, Input and Output, File Input/Output, Python Functions etc.

Course Content

Advance EXCEL

Microsoft Excel is a widely used tool for data analysis, reporting, and business work. This course provides practical training in data handling, calculations, analysis, and dashboard creation using real

EXCEL FOUNDATION

• Introduction to Excel and Spreadsheet Concepts

• Excel Interface and Workbook Structure

• Data Entry, Formatting, and Cell Management

• Rows, Columns, Sheets, and Tables

FORMULAS AND FUNCTIONS

• Basic Formulas and Calculations

• Arithmetic and Logical Formulas

• Cell Referencing (Relative, Absolute, Mixed)

• Common Functions (SUM, AVERAGE, COUNT, MIN, MAX)

• Logical Functions (IF, AND, OR, NOT)

• Text Functions (LEFT, RIGHT, MID, LEN, CONCAT)

• Date and Time Functions

Date and Time Functions

• VLOOKUP and HLOOKUP

• XLOOKUP Basics

• Nested Functions

• Error Handling Functions

DATA HANDLING AND CLEANING

• Sorting and Filtering Data

• Conditional Formatting

• Data Validation Rules

• Remove Duplicates

• Text to Columns

• Find and Replace

• Handling Missing and Incorrect Data

DATA ANALYSIS TOOLS

• Pivot Tables

• Pivot Charts

• Grouping and Summarizing Data

• Subtotals

• What-If Analysis

• Goal Seek and Scenario Manager

Course Content

SQL (Structured Query Language)

SQL (Structured Query Language) is a key tool used to manage and analyze data in modern organizations. This course provides practical training in MySQL and database operations for beginners.

Database Fundamentals

• Introduction to SQL and Relational Database Concepts

• Database Fundamentals and DBMS Overview

• Types of Databases

• SQL Command Categories (DDL, DML, DCL, DQL)

MYSQL Setup & Environment

• MySQL Environment Setup and Tools

• Working with MySQL Server and Interface

• Creating, Selecting, and Dropping Databases

Table & Structure Design

• Table Creation and Table Design Principles

• SQL Datatypes and Field Constraints

• Primary Keys, Foreign Keys

• Table Relationships

• Indexes and Basic Query Optimization

Data Operations (Core SQL)

• SQL Operators and Conditional Expressions • Data Insert Operations

• Update, Delete Records

• Select Queries

Filtering( Row, Group and Conditional)

• Where Clause

• Distinct

• Group By

• Having Clause

• Like

• In / Not in

• Like

Sorting & Result Control

• ORDER BY

• LIMIT

• OFFSET

Functions & Data Processing

• Aggregate and Statistical Functions

• String Functions

• Date Functions

• Numeric Functions

Joins & Multi-Table Queries

• Inner Join

• Left Join

• Right Join

• Full Join with UNION

Transaction Control

• AUTOCOMMIT MODE

• COMMIT COMMAND

Advance Queries

• Subqueries and Nested Queries

• Views and Virtual Tables

Advanced Database Features

• Stored Procedures

• Parameterized Logic

• ROLLBACK COMMAND

• Window Functions for Advanced Analysis

• Bulk Data Import and Export

Course Content

PYTHON

Python is a powerful and widely used language for data analysis, automation, and business tasks. This course provides practical training in Python basics along with NumPy and Pandas for efficient data handling and analysis.

Python Foundations

• Introduction to Python and programming fundamentals

• Features and advantages of Python language

• Python installation and interpreter setup

• Package manager (pip) basics

• Virtual environment setup basics

• Visual Studio Code installation

Core Language Basics

• Variables and variable naming rules

• Built-in data types (int, float, str)

• Type conversion functions

• Type checking methods

• Arithmetic operators

• Comparison operators

• Logical operators

• Membership operators

• Input functions

• Output and formatted printing

• String creation and indexing

• String slicing techniques

Control Flow & Logic

• if statement usage

• if-elif-else structures

• Nested conditions

• Multiple condition checking

• for loop iteration

Functions & Code Organization

• Function definition and calling

• Function parameters

• Default parameters

• Keyword arguments

• Return values

Data Structures

• List creation and methods

• List indexing and slicing

• List comprehension basics

• Tuple creation and properties

• Tuple unpacking

• Set creation and operations

• while loop execution

• range() function usage

• Loop control — break

• Loop control — continue

• pass statement

• Multiple return values

• Lambda functions

• Recursive functions basics

• Creating custom modules

• Importing modules

• Set methods

• Dictionary creation

• Dictionary keys and values

• Dictionary methods

• Nested data structures

Files & Error Handling

• Opening files

• File read operations

• File write operations

• File append mode

• Working with file paths

• Reading CSV/text data

• Exception types

• try statement

• except blocks

• finally block

• Raising custom exceptions

Course Content

NUMPY LIBRARY

NumPy Foundations

• Introduction to NumPy for numerical computing

• Features and advantages of NumPy

• NumPy vs Python lists performance difference

• Installing and importing NumPy

• Understanding ndarray structure

Array Creation

• Creating arrays from lists and tuples

• Using array() function

• Creating zero arrays (zeros)

• Creating one arrays (ones)

• Creating identity matrices

• Using arange() and linspace()

• Creating arrays with random values

Indexing & Slicing

• One-dimensional array indexing

• Multi-dimensional indexing

• Array slicing techniques

• Boolean indexing

• Fancy indexing

• Conditional selection

Vectorized Operations

• Element-wise arithmetic operations

• Vectorized calculations

• Array broadcasting in operations

Mathematical & Statistical Functions

• Aggregate functions (sum, mean, min, max)

• Axis-based calculations

• Comparison operations on arrays

• Logical operations on arrays

Reshaping & Transformation

• Reshaping arrays

• Flattening arrays

• Transpose operations

• Resize and reshape difference

Sorting & Filtering

• Sorting arrays

• Argsort and sort methods

• Filtering with conditions

• Where function usage

• Extracting filtered values

Course Content

PANDAS LIBRARY

Pandas Foundations

• Introduction to Pandas for data analysis workflows

• Features and advantages of Pandas library

• Installing and importing Pandas

• Understanding labeled data structures

Core Data Structures

• Series structure and creation methods

• DataFrame structure and components

• Creating DataFrames from lists and dictionaries

• Understanding index and column labels

• Data types

Data Import & Export

• Importing data from CSV files

• Importing data from Excel files

• Reading large datasets efficiently

• Exporting DataFrames to CSV

• Exporting DataFrames to Excel

Data Inspection & Exploration

• Viewing top and bottom records

• Dataset shape and structure checks

• Column information and data types

• Descriptive statistics summary

• Unique values and value count

Data Cleaning & Preparation

• Detecting data quality issues

• Data cleaning techniques

• Removing duplicates

• Renaming columns and labels

• Data type conversion

Missing Value Handling

• Identifying missing values

• Dropping missing records

• Filling missing values

Filtering & Selection

• Row and column selection

• Conditional filtering

• Boolean indexing

• Multi-condition filtering

• Query-based selection

Column Operations & Transformation

• Creating new columns

• Modifying existing columns • Column-wise calculations

• Applying transformation logic

• Mapping and replacing values

Grouping & Aggregation

• Group By operations

• Aggregation functions on groups

• Multi-column grouping

• Custom aggregation logic

Combining Datasets

• Merge operations on keys

• Join operations on index

• Concatenating datasets

• Handling overlapping columns

Sorting & Ranking

• Sorting by column values

• Multi-column sorting

• Ranking values within columns

Date & Time Processing

• Converting to datetime format

• Extracting date parts

• Time-based filtering

• Date range operations

Apply & Lambda Functions

• Apply function on columns

• Apply function on rows

• Lambda expressions in transformations

• Custom function application

Pivot & Summary Reporting

• Creating pivot tables

• Multi-level pivot reports

Course Content

Power BI

Power BI is a popular business intelligence and data visualization tool used to turn raw data into interactive dashboards and reports. This course provides practical training in Power BI for data modeling, visualization, and reporting for beginners.

Power BI Foundations

• Introduction to Business Intelligence concepts and analytics workflow

• Power BI Installation and setup process

• Power BI Desktop interface overview

• Understanding report, dataset, and workspace concepts

Data Connection & Loading

• Connecting to Excel data sources

• Connecting to CSV and text files

• Connecting to databases

• Multiple data source connections

Data Transformation (Power Query)

• Data transformation using Power Query

• Power Query Editor interface

• Data cleaning techniques

• Column splitting and merging

• Removing errors and duplicates

• Changing and detecting data types

• Data shaping and restructuring steps

DAX (Data Analysis Expressions)

• Introduction to DAX language

• DAX formula structure

• Common DAX functions

• Aggregation functions in DAX

• Filter context and row context basics

• Time intelligence functions

• Date-based calculations

Visual Creation & Tabular Visuals

• Creating charts and visual reports

• Bar and column charts

• Line and area charts

• Pie and donut charts

• Combo charts

• Table visuals

• Matrix visuals

• KPI visuals

• Cards and multi-row cards

Interactive Controls

• Filters at visual, page, and report level

• Slicers for interactive filtering

• Drill-up navigation

• Interactive visual behavior settings

Who can Join
this Course?

Valid Certificates in Multiple Fields

Stand out in Crowd

Access well Paying Growth

One Step Ahead with the Certifications

What Makes us Better

LIVE PROJECTS

EXPERT TRAINERS

HANDS ON TRAINING

MEMBERSHIP

TRAINING MODE

SMALL BATCH SIZE

FLEXIBLE TIMING

Technical Support

Affordable Fees

JOB Oriented Training

Globally Recognized
ISO Certified

100% Placement
Assistance

Meet your Mentors

Kuldeep Chhikara

Founder & Managing Director of Skynet ICA

Sahil

Senior Developer & Data Specialist

Santosh

Microsoft Certified Trainer

Vikas Bhaskar

E - Accountant

Harsh Utwal

"It is the one of the best institute in the world .it has hi-fi equipments and software in good condition and well -working . The teacher,s knowledge are well - qualified .
The condition of room is fully air conditioned and work and project are show on projector. Student are full filled with knowledge and skills."