What is Data Analytics?

     A well-curated data analytics course can begin you in the path of becoming a successful data analyst across different domains. The requirement for data professionals has grown exponentially across industries over the last decade, and undergoing data analytics training is one of the best customs of riding the tide.

     Be it analyzing a sporting event or detecting early-stage cancer; a data analyst has a position in everything. The scope of data analytics as a discipline has been rising since its inception. Every task, every method, every little gadget connected to the internet produces data that can be turned into vital information. The newfound utility of data has improved the importance of analytics and data science in India by manifolds. Therefore, a reputed data analytics certification course in India can boost your profession to get a flying start in the industry.

Why become a Data Analyst?

     The profession of Data analysis offers many rewards. As the volume of Data continues to raise globally, it is probable to reach at least 163 Zettabytes in 2025. Needless to say, Data Analysts will be gradually more in demand across all industries. This profession, therefore, offers many prospects for the future and development opportunities. A Data Analyst can liberally choose his sector of activity and even his company.

     In addition, there is a broad variety of specializations for Data Analysts: marketing, finance, and sales… depending on your interests and your favored sector, you can, therefore, also choose a specialty that suit you. Another strong point of this career concerns the salaries, which are tremendously attractive. The number of truly skilled Data Analysts is less than the demand from companies, so companies are ready to pay a lot for their services.

     It is also an exciting job in which your creativeness and your tactical mind will be called upon. You will enjoy the freedom to take the plan and use the tools of your choice to attain your goals. So, wait no longer; get yourself enroll in our Data Analytics course with placement.

Outcomes Of Data Analytics Certification In Bangalore

The main plan of the Analytics Training in Bangalore is to give you an outlook on the various techniques used in handle huge data sets via Data Analytics. Learners will be able to estimate the applications of these technologies, which are used to store and examine massive volumes of data. 

This Data Analyst Certification Course Training in Bangalore instruct the student on the various techniques used to examine structured and unstructured data. Creating visual tales with the apply  of Tableau and/or Power BI. 

The Data Analyst Course in Bangalore is the best course for professionals who want to acquire in-depth knowledge  on a daily basis used Data frameworks. The three-month Data Analytics training with Placement will cover necessary tools like SQL, NoSQL, Tableau, Power BI, and Advanced Excel concepts. 

Students will be trained how to store, retrieve, manipulate, and examine large datasets stored in Database management systems like relational database management systems or document-based database systems with an Analytics Course in Bangalore and Artificial Intelligence Course Training in Bangalore. They will also be trained several concepts for placing data on the serving layer in order to show findings in more simply digestible visual representations. 

The Data Analytics training with placement in Bangalore and Data Science Training in Bangalore contain multiple applied case studies that allow the participants. To work out complex business problems, improving profitability in their companies.

Advantages Of Data Analytics Course

It finds and fine-tunes flaws in datasets with the assist of data cleansing at Best Analytics Training Institute in Bangalore. It aids in the advance of data quality, which benefits both customers and organizations such as banks, insurance companies, and finance companies. Furthermore, it also profits organizations in the following ways:

  • It removes duplicate data from data sets, ensuing in significant RAM savings. This reduces the company’s operating cost.
  • It assist in displaying appropriate advertising on online shopping websites based on client purchase behavior and previous data.

Learning Objectives Of Analytics Training In Bangalore

     To gain the skills to collect and interpret the data through our Analytics Training in Bangalore. It will organize you to turn into job-ready in descriptive and inferential statistics, regression analysis, hypothesis testing, forecasting, data extracts, and data blending. You will also get understanding about data visualization techniques using Power BI and Tableau, and moreover recognize ways to organize data and design dashboards.

     Additionally, our Best Analytics Training Institute also focus on the non-tech workforce, offering an idea about technicalities. In the Data Analyst Certification Course Training in Bangalore, you will get hands-on practice to basic programming principles and practice appropriate modern analytics, data mining and machine learning.

     The Analytics Course in Bangalore offers you detailed understanding through demos and projects. After the end of the course from our Best Analytics Training Institute in Bangalore, you can state yourself to be a certified Data Analyst. In case, you want to grow more understanding than you can opt for Data Science training in Bangalore.

What does Data Analyst training consist of?

Our Data Analyst training regularly lasts between four and six weeks. During this period, you will be learned the essentials of working with Data, including cleaning and preparing Datasets for analysis. You will also learn how to use various tools and techniques to find trends and patterns. At last, you will find out how to communicate your outcome in a way that non-technical people understand.

By the finish of your training, you must have a good understanding of how Data analysis works and be able to execute basic analysis tasks capably.

How is data science course different from an analytics course?

     Data analytics is a subset of data science with a relatively smaller range of exploration. A data analytics certification training program prepare you for use descriptive and predictive data analysis and data collection, cleaning, and organizing.

     A data science training program focus on finding patterns in data, asking relevant questions, preparing the machine learning algorithms to respond those questions. You can prefer a course depending on your background, your level of knowledge, and of course, the expert counsel of the mentors.

     A career in data science or data analytics can have many facet. For instance,this course will help you grow to be a business analyst from scratch. A machine learning course will assist you to advance your knowledge of algorithms and predictive modeling.

Future growth in Data Analytics

     Due to enlarged use of social media, internet of things, Mobile gadgets transactional data, data storage is increasing greatly. This increased data, increased usage in a variety of industries creating need for correct data analysis for a improved expansion in business. Today almost all start ups, medium scale and large scale companies relying on Data Analysis, predictive modeling for forecasting development, data mining, data cleaning & reporting of data to gather important information from enormous volume of its data.

     India has got major potential in Data analytics field for expert Graduates /PG freshers with essential analytical skills, Analyst, Statistician, research professionals, experienced professionals who are looking for quick growth in conditions of pay package, future growth and secured profession across world.

Suitable Job Roles

Jr. Data Analyst

Data Analyst -Tableau

Business Analyst

Data Analyst - Python

Data Transformation Analyst

Who is eligible for studying Data Analytics in Bangalore?

Anyone who needs to be trained more about data science and analytics is welcome to enrol in the course. A Bachelor’s degree with at least 50% in general or an equivalent grade from a highly regarded university, ideally in the sciences or computer science, is the minimal requisite for admission to a postgraduate Data Analytics study.

What value does learning data analytics have?

  • Top organisations now prioritize data analytics.
  • Expanding employment options
  • Increasing salaries for data analytics expert
  • Big Data analytics is prevalent all over the place.
  • You will be capable to choose from a variety of job titles and be in charge of make decisions for the organisation

What kind of employment options are there after completing the Data Analytics Course in Bangalore?

Your initial service can be a junior analyst position if you’re new to the career of data analysis. You might be capable to find employment as a data analyst if you have some earlier experience with handy analytical skills.
  • Business Intelligence Analyst
  • Data Analyst
  • Quantitative Analyst
  • Data Analyst Consultant
  • Operations Analyst
  • Marketing Analyst
  • Data Scientist
  • Data Engineer
  • Project Manager
  • IT Systems Analyst

In this data analytics courses in Bangalore, you’ll study

  • To Learn the methods of data production
  • To Works with tools and methods for organised and unstructured data processing
  • To know how descriptive and predictive analytics vary
  • To Describe how data for research can be gathered and intended
  • For Analyze data using predictive methods and obtain knowledge from companies
  • To allow more rational strategic decisions using data-driven decision-making
  • To check if the analyses help your assumption
  • To identify the ways to use ML techniques to determine business problems in your work

Our Top Hiring Partner for Placements

Trishana Technologies provides placement opportunities for all the students/professionals who have taken our training programs.
  • So far, we’ve correctly placed more than 600+ students in top MNC’s such as IBM, CTS, HCL, DELL, ETC
  • Modules intended to meet global market requirements are skillfully planned
  • We've excellent skill in interview training and placement training for students
  • Exhaustive placement instruction to get to be familiar with the skills and skill necessary for career readiness
  • Active placement gateway which gives students the chance to begin their professions on the intended direction
  • Extensive placement instruction to get to recognize the skills and expertise essential for career readiness
  • Winding up your career and your understanding in the prior Placement training workshops
  • We help you with complete mock interviews and resume prep courses to build a professional approach among students.

FAQ

Data Analytics, Business Analytics, and Data Science have the identical meaning with just 3 different terminologies. The people working in this career are commonly called Data Analysts and they work on processing data, using frameworks, and algorithms to create actionable information and solve business problems. In Business Analytics and Data Analytics, you learn and examine data to generate information that helps solve problems. While in Data Science, you learn data to expect the future, build recommendation engine, mine data, etc.

Big data analysis requires the estimation of huge volumes of information. This would be intended to find the latent trends, similarities, and perspective so that planned decisions can be taken correctly.

In practice study, data scientists and analysts use technologies of data processing and organisations constantly use this technology to inform their decision making. The study of the data will help businesses recognize their clients better, analyse promotional campaigns, modify the content, construct content strategies and deliver products.

Industries have become data-driven. The demand for Data Scientists is rising exponentially, but at the same time, companies have become very cautious in hiring candidates in these roles. The industry wants data scientists who hold and can apply industry-relevant skills to resolve actual business problems.

After two to four years on the job, you can anticipate an average salary of $70,000. A senior analyst with around six years of practice commands a higher salary of about $88,000, but specialization can build the data analyst salary soar past the $100,000 mark.

Skills mandatory for data analytics

  • Structured Query Language (SQL)
  • Microsoft Excel
  • Critical Thinking
  • R or Python-Statistical Programming
  • Data Visualization.
  • Presentation Skills
  • Machine Learning.(ML)
  • Data Analyst.
  • Data Engineers
  • Database Administrator
  • Machine Learning Engineer
  • Data Scientist
  • Data Architect
  • Statistician
  • Business Analyst.

Syllabus

Introduction

MS office Versions(similarities and differences)

Interface(latest available version)

Row and Columns

Keyboard shortcuts for easy navigation

Data Entry(Fill series)

Find and Select

Clear Options

Ctrl+Enter

Formatting options(Font,Alignment,Clipboard(copy, paste special))

Referencing, Named ranges,Uses,Arithemetic Functions

Mathematical calculations with Cell referencing(Absolute,Relative,Mixed)

Functions with Name Range

Arithmetic functions(SUM,SUMIF,SUMIFS,COUNT,COUNTA,COUNTIFS,AVERAGE,AVERAGEIFS,MAX,MAXIFS,MIN,MINIFS)

Logical functions

Logical functions:IF,AND,OR,NESTED IFS,NOT,IFERROR

Usage of Mathematical and Logical functions nested together

Referring data from different tables: Various types of Lookup, Nested IF

LOOKUP

VLOOKUP

NESTED VLOOKUP

HLOOKUP

INDEX

INDEX WITH MATCH FUNCTION

INDIRECT

OFFSET

Advanced functions

Combination of Arithmatic

Logical

Lookup functions

Data Validation(with Dependent drop down)

Date and Text Functions

Date Functions:DATE,DAY,MONTH,YEAR,YEARFRAC,DATEDIFF,EOMONTH

Text Functions:TEXT,UPPER,LOWER,PROPER,LEFT,RIGHT,SEARCH,FIND,MID,TTC, Flash Fill

Data Handling::Data cleaning, Data type identification, Remove Duplicates, Formatting and Filtering

Number Formatting(with shortcuts)

CTRL+T(Converting into an Excel Table)

Formatting Table

Remove Duplicate

SORT

Advanced Sort

FILTER

Advanced Filter

Data Visualization: Conditional Formatting, Charts

Conditional formatting(icon sets/Highlighted colour sets/Data bars/custom formatting)

Charts:Bar,Column,Lines,Scatter,Combo,Gantt,Waterfall,pie

Data Summarization: Pivot Report and Charts

Pivot Reports:Insert,Interface,Crosstable Reports;Filter,Pivot Charts,

Slicers:Add,Connect to multiple reports and charts

Calculated field, Calculated item

Data Summarization: Dashboard Creation, Tips and Tricks

Dashboard:Types,Getting reports and charts together, Use of Slicers.

Design and placement: Formatting of Tables,Charts,Sheets,Proper use of Colours and Shapes

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Power Query: Interface, Tabs

Connecting to data from other excel files, text files, other sources

Data Cleaning

Transforming

Loading Data into Excel Query

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Using Loaded queries

Merge and Append

Insert Power Pivot

Similarities and Differences in Pivot and Power Pivot reporting

Getting data from databases, workbooks, webpages

VBA and Macros

View Tab

Add Developer Tab

Record Macro:Name,Storage

Record Macro to Format table(Absolute Ref)

Format table of any size(Relative ref)

Play macro by button

shape

as command(in new tab)

Editing Macros

VBA:Introduction to the basics of working with VBA for Excel: Subs, Ranges, Sheets

Comparing values and conditions

if statements and select cases

Repeat processes with For loops and Do While or Do Until Loops

Communicate with the end-user with message boxes and take user input with input boxes, User Form

Introduction to Mysql

Introduction to Databases

Introduction to RDBMS

Explain RDBMS through normalization

Different types of RDBMS

Software Installation(MySQL Workbench)

SQL Commands and Data Types

Types of SQL Commands (DDL,DML,DQL,DCL,TCL) and their applications

Data Types in SQL (Numeric, Char, Datetime)

DQL & Operators

SELECT

LIMIT

DISTINCT

WHERE AND

OR

IN

NOT IN

BETWEEN

EXIST

ISNULL

IS NOT NULL

Wild Cards

ORDER BY

Case When Then and Handling NULL Values

Usage of Case When then to solve logical problems and handling NULL Values (IFNULL, COALESCE)

Group Operations & Aggregate Functions

Group By

Having Clause

COUNT

SUM

AVG

MIN

MAX

COUNT String Functions

Date & Time Function

Constraints

NOT NULL

UNIQUE

CHECK

DEFAULT

Primary key

Foreign Key (Both at column level and table level)

Joins

Inner

Left

Right

Cross

Self Joins

Full outer join

DDL

Create

Drop

Alter

Rename

Truncate

Modify

Comment

DML & TCL Commands

DML

Insert

Update & Delete

TCL

Commit

Rollback

Savepoint

Data Partitioning

Indexes and Views

Indexes (Different Type of Indexes)

Views in SQL

Stored Procedures

Procedure with IN Parameter

Procedure with OUT parameter

Procedure with INOUT parameter

Function, Constructs

User Define Function

Window Functions

Rank

Dense Rank

Lead

Lag

Row_number

Union, Intersect, Sub-query

Union, Union all

Intersect

Sub Queries, Multiple Query

Exception Handling

Handling Exceptions in a query

CONTINUE Handler

EXIT handler

Triggers

Triggers – Before | After DML Statement

Introduction to Tableau

What is Tableau ?

What is Data Visulaization ?

Tableau Products

Tableau Desktop Variations

Tableau File Extensions

Data Types, Dimensions, Measures, Aggregation concept

Tableau Desktop Installation

Data Source Overview

Live Vs Extract

Basic Charts & Formatting

Overview of worksheet sections

Shelves

Bar Chart, Stacked Bar Chart

Discrete & Continuous Line Charts

Symbol Map & Filled Map

Text Table, Highlight Table

Formatting: Remove grid lines, hiding the axes, conversion of numbers to thousands, millions, Shading, Row divider, Column divider

Marks Card

Filters

What are Filters ?

Types of Filters

Extract, Data Source, Context, Dimension, Measure, Quick Filters

Order of operation of filters

Cascading

Apply to Worksheets

Calculations

Need for calculations

Types: Basic, LOD’s, Table

Examples of Basic Calculations: Aggregate functions, Logical functions, String functions, Tablea calculation functions, numerical functions, Date functions

LOD’s: Examples

Table Calculations: Examples

Data Combining Techniques

What is Data Combining Techniques ?

Types

Joins, Relationships, Blending & Union

Custom Charts

Dual Axis

Combined Axis

Donut Chart

Lollipop Chart

KPI Cards (Simple)

KPI Cards (With Shape)

Groups, Bins, Hierarchies, Sets, Parameters

What are Groups ? Purpose

What are Bins ? Purpose

What are Hierarchies ? Purpose

What are Sets ? Purpose

What are Parameters ? Purpose and examples

Analytics & Dashboard

Reference Lines

Trend Line

Overview of Dashboard: Tiled Vs Floating

All Objects overview, Layout overview

Dashboard creation with formatting

Dashboard Actions & Tableau Public

Actions: Filter, Highlight, URL, Sheet, Parameter, Set

How to save the workbook to Tableau Public website ?

Power BI Introduction and Installation

Understanding Power BI Background

Installation of Power BI and check list for perfect installation

Formatting and Setting prerequisits

Understanding the difference between Power BI desktop & Power Query

The Power BI user interface, including types of data sources and visualizations

Getting familiar with the interface BI Query & Desktop

Understanding type of Visualisation

Loading data from multiple sources

Data type and the type of default chart on drag drop.

Geo location Map integration

Sample dashboard with Animation Visual

Finanical sample data in Power BI

Preparing sample dashboard as get started

Map visual Types and usages in different variation

Understanding scatter Plot chart with Play axis and the parameters

Power BI artificial intelligence Visual

Understanding the use of AI in power BI

AI analysis in power bi using chart

Q&A chat bot and the use in real life

Hirarchy tree

Power BI Visualization

Understanding Column Chart

Understanding Line Chart

Implementation of Conditional formating

Implementation of Formating techniques

Power Query Editor

Loading data from folder

Understanding Power Query in detail

Promote header, Split to limiter, Add columns, append, merge queries etc

Modelling with Power BI

Loading multiple data from different format

Understanding modelling (How to create relationship)

Connection type, Data cardinality, Filter direction

Making dashboard using new loaded data

Power Query Editor Filter Data

Power Query Custom Column & Conditional Column

Manage Parameter

Introduction to Filter and types of filter

Trend analysis, Future forecast

Customize the data in Power BI

Understanding Tool tip with information

Use and understanding of Drill Down

Visual interaction and customisation of visual interaction

Drill through function and usage

Button triggers

Bookmark and different use and implementation

Navigation buttons

Dax Expressions

Introduction to DAX

Table Dax, Calculated column, DAX measure and difference

Eg:- Calendar, Calendar auto, Summarize, Group by etc

Calculated Column

Related, Lookup value, switch, Datedif,Rankx,Date functions

Dax Measure and Quick Measure

Remove filters, Keep filters, All, Allselected, Time Intelligence Functions,Rolling average,YoY, Running total

Custom Visual

Custom visual and understanding the use of custom

Loading custom visual, Pinning visual

Loading to template for future use

Publishinhg Power Bi

Power BI Service

Introduction to app.powerbi.com

Schedule refresh

Data flow and use power bi from online

Download data as live in power point and more

Anaconda Installation,Introduction to python,Data types,Opearators

Variables,data types(integer,Boolean,Float,List,tuple,string),Opearators in python

Data types Contd,Slicing the data,Inbuilt functions in python

Dictionaries,Sequence methods,Concatenate,Repetition,len,min,max functions,Index position,Addition and deletion of elements,Reverse,Sorting

Sets,Set Theory,Regular Expressions,Decision making statements

Sets,re module(findall,search,split,match),if,elifGetting input from user,Identity Operators

Loops,Functions,Lambda functions,Modules

For,While loops,Functions,Lambda functions,Math module,Calender module,Date & time module

Pandas,Numpy,Matplotlib,Seaborn

Data frame creation using different methods,Using Pandas anlysis on Universities,Salary data sets,Visualization using Matplotlib and Seaborn,Numpy introduction

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