Best MIS & Data Analyst Training Institute in Noida - GVT Academy

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Data Analytics | Business Analytics | Data Science For Fresher 1.5 to 3 Months Internship Certification Offline / Online Live Classes with Recording Advanced & Master Course of Data & Business Analytics Module 1. Advanced Excel with MIS Reporting  Module 2. SQL  Module 3. Power BI  Module 4. Python  Module 5. HR Round of Interview

Program Benefits

Industry acceptable Data Analytics Certification for all learner’s training which help fresher/experienced to up-skill in companies

Industry Expert Sr. Lead Analyst / Technical Analyst with 13+ Years provide workshop session @ GVT Academy

After completion of 70% Data Analytics Training our dedicated placement team arrange interview till placement.

Data Analytics Practical Training helps to gain exposure like corporate level with technical test series

Real time projects & best case study makes workshop is very unique and lively for learners.

For Learner’s, our admin team fresh batch schedule/re-scheduling classes/arrange doubt classes.

Detail Live Project Based Course Content

Data Analytics/Business Analytics

Module-1 Basic & Advanced Excel

Introduction to Excel

• Basic Understanding Menu and Toolbar

• Introduction to different category of functions

• Basics, Mathematical and Statistical

• Date and Time, Logical

• Lookup and References

• Text and Information.

Mathematical Functions

• Sum, Sumif, Sumifs,

• Count, Counta, Countblank, Countif, Countifs

• Average, Averagea, Averageif, Averageifs,

• Subtotal, Aggregate, Rand, Randbetween,

• Roundup, Rounddown, Round, Sumproduct

Date & Time Function

• Date, Day, Month, Year,

• Edate, Eomonth, Networkdays,

• Workday, Weeknum, Weekday,

• Hour, Minute, Second,

• Now, Today, Time

Text Functions & Data Validation

• Char, Clean, Code, Concatenate

• Find, Search, Substitute, Replace

• Len, Right, Left, Mid, Lower, Upper, Proper, Text, Trim, Value, Large

• Small Filters (Basic, Advanced, Conditional)

• Sort (Ascending, Descending, Cell/ Font Color)

• Conditional Formatting,

• Data Validation, Group & Ungroup

• Data split

Statistical Function & Other Functions

• Isna, Isblank, Iserr, Iseven, Isodd, Islogical, Isytext

• Max, Min, Len, Right, Left

• Mid, ,Maxa, Maxifs, Median, Minifs, Mina

• Vara, Correl

• Logical Function

• And

• Or

• If

• Iferror

• Not

• Nested If

Lookup & Reference Functions

• VLookup, HLookup, Index, Match,

• Offset, Indirect, Address,

• Column, Columns, Row, Rows, Choose,

• Arrays Concept In Lookup Formula’s,

• Past Special, Past link

Pivot Table - MIS, Data Analysis & Visualization

• Pivot Table

• What-if Analysis

• Data Table –One Variable and Two Variables,

• Data Analysis Using Statistics, Descriptive Statistics

• ANOVA

• Moving Average, Testing Hypothesis,

• Measuring Covariance and Correlation

• Distribution, Regression

• Graphs & Charts

• Analysis Tool Pack, Solver, Histogram, Pareto, Water Fall,

• Import and Export data

• Protect/Unprotect sheets/workbooks

• Worksheet formatting and Print Display

Data Collection Method

• With Data Quality, Collaboration & Security Like Share Your Workbook On Share Drive With Quality

Analysis Single/Multidimensional Analysis

• Like Three Dimensional (3D) Tables

• Sensitive Analysis Like Data Table

• Manual What-If Analysis

• Threshold Values

• Goal Seek

• One-Variable Data Table

• Two-Variable Data Table

Advanced Dashboard in Excel

• Overview of Chart types

• Chart Formatting

• Active X Form Controls

• Principle of great dashboard design

• Selecting Correct Chart to display data

• Interactive Charts with Form Controls

• Combo box, Check Box, Scroll Bar and Radio Button

• Interactive Dashboard with Form Controls, Form Controls for reports automation

• Data Modeling

Google Sheet – 2 Classes

25+ Excel Assignments Two Live Projects

Module-2- SQL

Introduction

• SQL Overview

• What is SQL?

• Installing the test environment

• Editors and Platforms to learn SQL

Complete SQL in a Class

• Introduction

• Quick-start

• Using the basic SELECT statement

• Selecting rows

• Selecting columns

• Counting rows

• Inserting data

• Updating data

• Deleting data

• Import and Export data

Fundamentals of SQL

• Databases and Tables

• SQL Syntax

• Data Definition

• Data Manipulation

• Data Control

• Transactional Control statements

• Creating tables

• Deleting a table

• Inserting rows into a table

• Deleting rows from a table

• What is NULL?

• Controlling column behaviors with constraints

• Changing a schema with ALTER

• Filtering data with WHERE, LIKE, and IN

• Removing duplicates with SELECT DISTINCT

• Sorting with ORDER BY

How Relationships Work in SQL

• Understanding joins

• Accessing related tables with JOIN

• Multiple related tables

Explaining SQL Strings

• About SQL strings

• Finding the length of a string

• Selecting part of a string

• Removing spaces with TRIM

• Making strings uppercase and lowercase

Number & SQL

• About numeric types

• Finding the type of a value

• Integer division and remainders

• Rounding numbers

SQL Functions and Clause

• The Aggregate functions

• MIN

• MAX

• AVG

• SUM and COUNT

• UPPER

• LENGTH

• LOWER

• The GROUP BY and HAVING clauses

• Grouping in a combination with joining

Triggers in SQL

• Concept of Trigger

• Create Trigger for:

• Insert

• Update

• Delete

• Alter Trigger

What are Sub-selects and Views in SQL

• Creating a simple sub-select

• Searching within a result set

• Creating a view

• Creating a joined view

Maintaining SQL Server Data Base

• Backup Database

• Restore Database

SQL Server Job Creation

• How to create job in SQL Server Agent

• How to schedule job

Live Project

Module-3-Data Visualization- MS Power BI

Microsoft Power BI – Introduction

• What is MSPBI & Scope

• Learn the common work flow in Power BI

• Building blocks of Power BI and its relations

• Quick demo how to create a business dashboard in MSPBI

• MSPBI components

MS Power BI - Getting Business Data

• Get data in shape for use with Power BI

• Combining two or more data sets (source data) for reporting

• Tackling messy data in MS Power BI

• Clean & Transform data

MS Power BI -Data Visualization

• Create and customize visualization

• Use combination charts

• Create and format slicers

• Map visualizations

• Visualizations utilization

• Use tables and matrixes

• Long live bubbles

• scatter charts in action

• Advanced funnel and waterfall charts

• Drive fast dashboard insights with gauges and numbers

• Color your visualization world with colors

• shapes and scales

• Adding personal touch

• logo etc. to reports and dashboards

• Display and present your dashboard in a way you want with summarize data

• Control how your report elements overlap with each other

• Learn to drill into hierarchies

• Manage how levels are shared (Z-order in reports)

• How to use R visuals in MSPBI

MS Power BI - Data Exploring & Sharing

• Quick insights in Power BI Service

• Create and configure a dashboard

• Share dashboard with your organization

• Display and edit visuals- tiles

• full screen

• Get more space on your dashboard

• Install and configure a personal gateway

• Excel and MSPBI

• Import and excel table into Power BI

• Import excel files with data models and power view sheets

• Connect One Drive for business to MSPBI

• Excel data in Power BI summary

MS Power BI - DAX (Data Analysis Expression) Application

Setting up Data Models with DAX

• DAX for creating tables and columns

• Rows vs. query vs. filter context

• DAX for calculated tables and columns

• Creating a date table

• Calculated column for costs

• Data cleaning with DAX

• Connecting data from different tables

• Methods to create DAX measures

• Advantages of explicit measures V2

• DAX and measures

• Using variables

• Basic statistical measures

• Quick measures

Power BI - Common DAX Measures

• Filtering and counting with DAX

• Understanding different filter functions

• Using different filters with DAX

• Filter ALL the data

• Calculating with a filter

• Analyzing across dimensional tables

• Iterating functions

• DIY iterating functions

• Iterating functions in Power BI

• Practice with iterating functions

• More iterating functions

• Use of RANKX()

Power BI - Redefine DAX

• Logical functions

• Interpreting SWITCH()

• Logical functions in Power BI

• IF() for formatting tables

• Exploring SWITCH()

• Grouping

• Row-level security

• Applying row-level security

• Managed roles in Power BI

• Creating an email list

• Implementing RLS

Power BI

- Advanced DAX

• Table manipulation functions

• Summary of SUMMARIZE()

• Table manipulations using DAX

• SUMMARIZE() the facts

• ADDCOLUMNS()? No problem!

• Time intelligence functions

• Time intelligence functions output

• Time intelligence in Power BI

• Use of TOTALYTD()

• Use of SAMEPERIODLASTYEAR()

Module-4- Python Data Science

Python Data Science – An Introduction

• Data types : int, float, str etc

• Operations on data types

• Data structures: list, dict, tuples, set

• Iterators/iterables

• functions

• Pandas Dataframe, NumPy arrays

• Data manipulation in pandas: slicing, subset, cross tabulation, aggregation

Python - Reference Data for running example

• XYZ Company Dataset

• Titanic

Python - Data Exploration

• Univariate Statistics: mean, median, std.

• Bivariate Statistics : correlation , covariance

• Plots using Matplotlib, seaborn

• Concepts of inferential statistics

• Standardization

• log transform

• Dummy variable creation

Python - Dimensionality Reduction + Linear Transformation

• PCA

• LDA

• Matrix

• Determinant

• Matrix multiplication

• Element wise operations

Python - Supervised Learning

• Linear classifier: logistic regression

• Linear classifier: Support Vector Classifier

• Tree Classifier: Decision Trees

• Ensemble Classifier: RF, Boosted Trees

• Cost Function minimization

• Scikit learn library

• Regression

Python - Machine Learning Concepts

• Bias , Variance

• Regularization

• Hyperparameter tuning

• Parametric

• Non parametric methods

• cross validation

• Sampling data

Python- Introduction to Deep Learning

• Understanding a perceptron

• Forward propagation

• Backward propagation

• Parameter update

• CNN

• Regularization: dropout, data augmentation

• Optimization: Momentum, Adam, AdamW

• Data loading

• gradient descent

Python- Framework

• PyTorch

Module-5- HR Round Interview Preparation

 Tell me about yourself

 Tell me about the gap in your resume

 How has your skills & experience prepared you for this role?

 How would you rate yourself on a scale of 1 to 10?

 What are your greatest strengths and weaknesses?

 What is your biggest achievement so far?

 What do you know about the company?

 Where do you see yourself in 5 years?

 What are your salary expectations?

 Why are you looking for a change?

 How do you handle stress and pressure?

After Completion of 80% Course We Offer

Resume Designing Services

Mock up Interview

Daily Assignments

Data for Practice

Video Recording

Interview Questions

Offline & Online Classes

Weekdays Weekends Classes Available

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