What are the different types of Data Analytics?

Descriptive. Diagnostic. Predictive. Prescriptive. Cognitive.

Why choose the Croma campus for the Data Analyst course in Gurgaon?

An ISO Certified. End-to-end session. Personalized sessions.

What are the tools of Data Analytics?

There are multiple tools get out for completing the processes of Data Analytics.

How do you collect data?

Surveys. Transactional tracking. Interview or Focus Groups. Observation. Online Tracking.

In an SQL server, there are various rows, columns, expressions as well as a parameters.

Data Analytics Course in Gurgaon

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Data Analytics helps out the organization for analyzing data from a different perspective which consists out real-time, historical, unstructured, etc. It helps out in connecting the automated decisions for increasing our business intelligence throughout the organization. But today there is the best solution support given to the organizations for increasing their end-to-end encryption. Resultantly, the demand for Data Analytics Training in Gurgaon spending up.
However, it helps out organizations digitally transform their activities for emerging as more productive. Additionally, it assists in optimizing operations related to daily business activities. Increasing collaboration between different businesses also makes out things easier to adapt. Data scientists can also work with the customers to help them in handling their real-time problems. But it is important to gather information regarding the Data Analytics Training Institute in Gurgaon.

The course offers an overview of Big Data and helps out the candidates in assisting with different complicated procedures. Moreover, emphasizes a variety of Analytics things needed to make out organization efficient. Additionally, Data Analyst Training in Gurgaon increasing its demand;

Explaining the various realms of Data Analytics.

Differentiating between various data roles.

Understanding the different components of Data analytics.

Handling out different types of data structures.

Getting well-adapted to various roles in the industry.

After completing the Data Analyst Course in Gurgaon the salary gets out in the range of Rs 1.8 lakh to Rs 11.9 lakh. Moreover, as per the reports of the ambition box, the average salary gets struck out at the rate of 15 lakh per annum.

Getting out of a job in Data Analytics is the first step in growing out of the career in the domain of Data Analytics. In case you have no previous experience in this domain then you can go through the below-mentioned course prospects after Data Analytics Training in Gurgaon;

Data Analytics gets highly leveraged by startups as well as large organizations. It assists in improving customer experience, targeted marketing & optimizing resources.

If we talk about DataOps which defines the streamlining of operations. Thus, managing a large amount of data becomes important for getting out actionable insights.

Due to the high demand for data, it is becoming the term for new service. It offers widespread solutions for purposes of data integration, analyzing data, etc.

Overall the data analysts have multiple sets of skills as they are good at working with the numbers & reports. Moreover, they use strong presentation skills which can easily appease the customers.

Technology companies change out rapidly with the organizational procedures taking place. Departments are constantly adapting to the new changes which are taking place inside the industrial verticals.

Undoubtedly, everyone heard about Data Analytics in modern businesses because they are responsible for handling organizational functions. Simply, data analytics is critical to handling organizational projects. As the Data Analyst training in Gurgaon gets completed you have to overcome the reasons behind its popularity:

The latest research performed by indeed.com and others proves out there is an increasing trend in the domain of Data Analytics which proves to increase the number of job opportunities.

The current for Data Science is seeking out increase due to the advent of new technologies in ongoing businesses. Moreover, businesses are adopting cloud infrastructure & workloads.

Moreover, automation of the data analysts gets considerable useful for businesses when organization deals with big data. Organizations are adopting new techniques.

Data Analytics contributes out through multiple processes of businesses with the help of data exploration, data preparation, and data automation as well among others.

Data analytics takes out the operational control of businesses moreover with the help of continuous involvement of data in business processes it is getting acceleration.

Data analysts are the professionals who get responsible for the senior leadership in the organization who make out strategic decisions. After completing the course from the Data Analytics training institute in Gurgaon you have to follow the below-mentioned primary duties:

Using the statistical methods for analyzing data & generating business reports.

Working with the management team to create a prioritized list of the business segment.

Identifying & recommending new ways for saving money as well as streamlining business operations.

Using out the data trends in the customer base as well as consumer population for the whole.

Working with the departmental managers for outlining the specific data according to the business method.

After completing the Data Analyst training in Gurgaon multiple organizations will get to hire out from the pool of candidates. If we talk regarding the organizations then it is Infogain Solutions Pvt Ltd, PubMatic, Serving Skill, Reliance Retail, Huquo Consulting Pvt Ltd, Wipro, CBRE, etc.

While completing the Data Analytics Course in Gurgaon you get out personalized training with specialized faculty members. Moreover, you also get out 100% globally recognized training certificate which will boost the chances of getting a job in a competitive market.

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Why should you learn Data Analytics?

The outburst of data transforming the businesses.

Helping out businesses to adapt to the new trends.

Data scientists have a tremendous impact on businesses.

It aims to capture out with the development technology.

Opens out the door for various opportunities in corporate.

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CURRICULUM & PROJECTS

Data Analytics Training Program

Introduction

What is Data Analytic

Common Terms in Data Analytics

What is data

Classication of data

Relevance in industry and need of the hour

Types of problems and business objectives in various industries

How leading companies are harnessing the power of analytics

Critical success drivers.

Overview of Data Analytics tools & their popularity.

Data Analytics Methodology & problem-solving framework.

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Understanding Concepts of Excel

Creation of Excel Sheet Data

Range Name, Format Painter

Conditional Formatting, Wrap Text, Merge & Centre

Sort, Filter, Advance Filter

Different type of Chart Creations

Auditing, (Trace Precedents, Trace Dependents)Print Area

Data Validations, Consolidate, Subtotal

What if Analysis (Data Table, Goal Seek, Scenario)

Solver, Freeze Panes

Various Simple Functions in Excel(Sum, Average, Max, Min)

Real Life Assignment work

Ms Excel Advance

Advance Data Sorting

Multi-level sorting

Restoring data to original order after performing sorting

Sort by icons

Sort by colours

Lookup Functions

Subtotal, Multi-Level Subtotal

Grouping Features

Consolidation With Several Worksheets

Filter

Printing of Raw & Column Heading on Each Page

Workbook Protection and Worksheet Protection

Specified Range Protection in Worksheet

Excel Data Analysis

Data Table

Pivot Table

Generating MIS Report In Excel

Text Functions

Lookup & Reference Function

Logical Functions & Date and Time Functions

Database Functions

Statistical Functions

Financial Functions

Functions for Calculation Depreciation

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SQL Server Fundamentals

SQL Server 2019 Installation

Service Accounts & Use, Authentication Modes & Usage, Instance Congurations

SQL Server Features & Purpose

Using Management Studio (SSMS)

Conguration Tools & SQLCMD

Conventions & Collation

SQL Server 2019 Database Design

SQL Database Architecture

Database Creation using GUI

Database Creation using T-SQL scripts

DB Design using Files and File Groups

File locations and Size parameters

Database Structure modications

SQL Tables in MS SQL Server

SQL Server Database Tables

Table creation using T-SQL Scripts

Naming Conventions for Columns

Single Row and Multi-Row Inserts

Table Aliases

Column Aliases & Usage

Table creation using Schemas

Basic INSERT

UPDATE

DELETE

SELECT queries and Schemas

Use of WHERE, IN and BETWEEN

Variants of SELECT statement

ORDER BY

GROUPING

HAVING

ROWCOUNT and CUBE Functions

Data Validation and Constraints

Table creation using Constraints

NULL and IDENTITY properties

UNIQUE KEY Constraint and NOT NULL

PRIMARY KEY Constraint & Usage

CHECK and DEFAULT Constraints

Naming Composite Primary Keys

Disabling Constraints & Other Options

Views and Row Data Security

Benets of Views in SQL Database

Views on Tables and Views

SCHEMA BINDING and ENCRYPTION

Issues with Views and ALTER TABLE

Common System Views and Metadata

Common Dynamic Management views

Working with JOINS inside views

Indexes and Query tuning

Need for Indexes & Usage

Indexing Table & View Columns

Index SCAN and SEEK

INCLUDED Indexes & Usage

Materializing Views (storage level)

Composite Indexed Columns & Keys

Indexes and Table Constraints

Primary Keys & Non-Clustered Indexes

Stored Procedures and Benets

Why to use Stored Procedures

Types of Stored Procedures

Use of Variables and parameters

SCHEMABINDING and ENCRYPTION

INPUT and OUTPUT parameters

System level Stored Procedures

Dynamic SQL and parameterization

System functions and Usage

Scalar Valued Functions

Types of Table Valued Functions

SCHEMABINDING and ENCRYPTION

System Functions and usage

Date Functions

Time Functions

String and Operational Functions

ROW_COUNT

GROUPING Functions

Triggers, cursors, memory limitations

Why to use Triggers

DML Triggers and Performance impact

INSERTED and DELETED memory tables

Data Audit operations & Sampling

Database Triggers and Server Triggers

Bulk Operations with Triggers

Cursors and Memory Limitations

Cursor declaration and Life cycle

STATIC

DYNAMIC

SCROLL Cursors

FORWARD_ONLY and LOCAL Cursors

KEYSET Cursors with Complex SPs

Transactions Management

ACID Properties and Scope

EXPLICIT Transaction types

IMPLICIT Transactions and options

AUTOCOMMIT Transaction and usage

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Introduction to Power BI

Overview of BI concepts

Why we need BI

Introduction to SSBI

SSBI Tools

Why Power BI

What is Power BI

Building Blocks of Power BI

Getting started with Power BI Desktop

Get Power BI Tools

Introduction to Tools and Terminology

Dashboard in Minutes

Interacting with your Dashboards

Sharing Dashboards and Reports

Power BI Desktop

Power BI Desktop

Extracting data from various sources

Workspaces in Power BI

Power BI Data Transformation

Data Transformation

Query Editor

Connecting Power BI Desktop to our Data Sources

Editing Rows

Understanding Append Queries

Editing Columns

Replacing Values

Formatting Data

Pivoting and Unpivoting Columns

Splitting Columns

Creating a New Group for our Queries

Introducing the Star Schema

Duplicating and Referencing Queries

Creating the Dimension Tables

Entering Data Manually

Merging Queries

Finishing the Dimension Table

Introducing the another DimensionTable

Creating an Index Column

Duplicating Columns and Extracting Information

Creating Conditional Columns

Creating the FACT Table

Performing Basic Mathematical Operations

Improving Performance and Loading Data into the Data Model

Modelling with Power BI

Introduction to Modelling

Modelling Data

Manage Data Relationship

Optimize Data Models

Cardinality and Cross Filtering

Default Summarization & Sort by

Creating Calculated Columns

Creating Measures & Quick Measures

Data Analysis Expressions (DAX)

What is DAX

Data Types in DAX

Calculation Types

Syntax, Functions, Context Options

DAX Functions

Measures in DAX

Measures and Calculated Columns

ROW Context and Filter Context in DAX

Operators in DAX - Real-time Usage

Quick Measures in DAX - Auto validations

In-Memory Processing DAX Performance

Power BI Desktop Visualisations

How to use Visual in Power BI

What Are Custom Visuals

Creating Visualisations and Colour Formatting

Setting Sort Order

Scatter & Bubble Charts & Play Axis

Tooltips and Slicers, Timeline Slicers & Sync Slicers

Cross Filtering and Highlighting

Visual, Page and Report Level Filters

Drill Down/Up

Hierarchies and Reference/Constant Lines

Tables, Matrices & Conditional Formatting

KPI's, Cards & Gauges

Map Visualizations

Custom Visuals

Managing and Arranging

Drill through and Custom Report Themes

Grouping and Binning and Selection Pane, Bookmarks & Buttons

Data Binding and Power BI Report Server

Introduction to Power BI Dashboard and Data Insights

Why Dashboard and Dashboard vs Reports

Creating Dashboards

Conguring a Dashboard Dashboard Tiles, Pinning Tiles

Power BI Q&A

Quick Insights in Power BI

Direct Connectivity

Custom Data Gateways

Exploring live connections to data with Power BI

Connecting directly to SQL Server

Connectivity with CSV & Text Files

Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel

Content packs

Update content packs

Publishing and Sharing

Introduction and Sharing Options Overview

Publish from Power BI Desktop and Publish to Web

Share Dashboard with Power BI Service

Workspaces (Power BI Pro) and Content Packs (Power BI Pro)

Print or Save as PDF and Row Level Security (Power BI Pro)

Export Data from a Visualization

Export to PowerPoint and Sharing Options Summary

Refreshing Datasets

Understanding Data Refresh

Personal Gateway (Power BI Pro and 64-bit Windows)

Replacing a Dataset and Troubleshooting Refreshing

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Introduction To Python

Installation and Working with Python

Understanding Python variables

Python basic Operators

Understanding the Python blocks.

Python Keyword and Identiers

Python Comments, Multiline Comments.

Python Indentation

Understating the concepts of Operators

Introduction To Variables

Variables, expression condition and function

Global and Local Variables in Python

Packing and Unpacking Arguments

Type Casting in Python

Byte objects vs. string in Python

Variable Scope

Python Data Type

Declaring and using Numeric data types

Using string data type and string operations

Understanding Non-numeric data types

Understanding the concept of Casting and Boolean.

Strings

List

Tuples

Dictionary

Sets

Control Structure & Flow

Statements if, else, elif

How to use nested IF and Else in Python

Loops

Loops and Control Statements.

Jumping Statements Break, Continue, pass

Looping techniques in Python

How to use Range function in Loop

Programs for printing Patterns in Python

How to use if and else with Loop

Use of Switch Function in Loop

Elegant way of Python Iteration

Generator in Python

How to use nested Loop in Python

Use If and Else in for and While Loop

Examples of Looping with Break and Continue Statement

How to use IN or NOT IN keyword in Python Loop.

Python Function, Modules and Packages

Python Syntax

Function Call

Return Statement

Arguments in a function Required, Default, Positional, Variable-length

Write an Empty Function in Python pass statement.

Lamda/ Anonymous Function

*args and **kwargs

Help function in Python

Scope and Life Time of Variable in Python Function

Nested Loop in Python Function

Recursive Function and Its Advantage and Disadvantage

Organizing python codes using functions

Organizing python projects into modules

Importing own module as well as external modules

Understanding Packages

Random functions in python

Programming using functions, modules & external packages

Map, Filter and Reduce function with Lambda Function

More example of Python Function

List

What is List.

List Creation

List Length

List Append

List Insert

List Remove

List Append & Extend using + and Keyword

List Delete

List related Keyword in Python

List Revers

List Sorting

List having Multiple Reference

String Split to create a List

List Indexing

List Slicing

List count and Looping

List Comprehension and Nested Comprehension

Tuple

What is Tuple

Tuple Creation

Accessing Elements in Tuple

Changing a Tuple

Tuple Deletion

Tuple Count

Tuple Index

Tuple Membership

TupleBuilt in Function (Length, Sort)

Dictionary

Dict Creation

Dict Access (Accessing Dict Values)

Dict Get Method

Dict Add or Modify Elements

Dict Copy

Dict From Keys.

Dict Items

Dict Keys (Updating, Removing and Iterating)

Dict Values

Dict Comprehension

Default Dictionaries

Ordered Dictionaries

Looping Dictionaries

Dict useful methods (Pop, Pop Item, Str , Update etc.)

Sets

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Frozen Sets

Strings

What is Set

Set Creation

Add element to a Set

Remove elements from a Set

PythonSet Operations

Python Exception Handling

Python Errors and Built-in-Exceptions

Exception handing Try, Except and Finally

Catching Exceptions in Python

Catching Specic Exception in Python

Raising Exception

Try and Finally

Python File Handling

Opening a File

Python File Modes

Closing File

Writing to a File

Reading from a File

Renaming and Deleting Files in Python

Python Directory and File Management

List Directories and Files

Making New Directory

Changing Directory

Python Database Interaction

SQL Database connection using

Creating and searching tables

Reading and Storing cong information on database

Programming using database connections

Reading an excel

Working With Excel

Reading an excel le using Python

Writing to an excel sheet using Python

Python| Reading an excel le

Python | Writing an excel le

Adjusting Rows and Column using Python

ArithmeticOperation in Excel le.

Play with Workbook, Sheets and Cells in Excel using Python

Creating and Removing Sheets

Formatting the Excel File Data

More example of Python Function

Complete Understanding of OS Module of Python

Check Dirs. (exist or not)

How to split path and extension

How to get user prole detail

Get the path of Desktop, Documents, Downloads etc.

Handle the File System Organization using OS

How to get any les and folders details using OS

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Data Analysis and Visualization using Pandas.

Statistics

Pandas

Data Analysis and Visualization using NumPy and MatPlotLib

NumPy

MatPlotLib

Introduction to Data Visualization with Seaborn

Introduction to Seaborn

Visualizing Two Quantitative Variables

Visualizing a Categorical and a Quantitative Variable

Customizing Seaborn Plots

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Capstone Project

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+ More Lessons

Course Design By

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Course Offered By

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