Analytics Landscape and Careers

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Industry Landscape. BIG. DATA. Data that is . TOO LARGE . & . TOO . COMPLEX . for conventional data tools to capture, store and analyze.. Shares traded on US Stock Markets each day:. 7 Billion. Data generated in one flight from NY to London:. ID: 738907 Download Presentation

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Analytics Landscape and Careers




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Presentations text content in Analytics Landscape and Careers

Slide1

Analytics Landscape and Careers

Slide2

Industry Landscape

Slide3

BIG

DATA

Data that is

TOO LARGE

&

TOO

COMPLEX

for conventional data tools to capture, store and analyze.

Shares traded on US Stock Markets each day:

7 Billion

Data generated in one flight from NY to London:

10 Terabytes

Number of tweets per day on Twitter:

400 Million

Number of ‘Likes’ each day on Facebook:

3 Billion

The 3V’s of Big Data

VOLUME

VARIETY

VELOCITY

90

%

OF THE WORLD’S DATA WAS GENERATED IN THE

LAST TWO YEARS

Big Data Everywhere!

www.imarticus.org

3

Slide4

What is

Analytics?

Data on its own is useless unless you can make sense of it!

WHAT IS ANALYTICS?

The

scientific process of transforming data into insight for making better decisions, offering new opportunities for a competitive

advantage

www.imarticus.org

4

Slide5

The Case for Business Analytics

The Business environment today is more complex than ever before.

Businesses are expected to be diligently responsive to the increasing demands of

customers,

various stakeholders and even regulators.

Organizations have been turning to the use of analytics.

More than 83% of Global CIOs surveyed by IBM in 2010 singled out Business Intelligence and Analytics as one of their visionary plans for enhancing competitiveness.

In most cases the primary objective of an organization that seeks to turn to analytics is:

Revenue/Profit growth

Optimize expenditure

SOLUTION

BUSINESS NEED

GOAL

www.imarticus.org

5

Slide6

Types of Analytics

1

3

2

Analytics

Prescriptive Analytics

Descriptive analytics

Predictive analytics

Enabling

smart decisions

based

on

data

What should we do

?

Mining

data to provide

business insights

What has happened?

Predicting the future based on historical

patternsWhat could happen?

www.imarticus.org

6

Slide7

Types of Analytics

Prescriptive Analytics

advice on possible outcomes

Predictive

Analytics

understanding the future

Descriptive

Analytics

insight into the

past

Why do airline prices change every hour?

How do grocery cashiers know to hand you coupons you might actually use?

How does Netflix frequently recommend just the right movie?

www.imarticus.org

7

Slide8

Growing Need for

Analytics

DATA HARNESSING

Companies store each piece of information generated during the business operations and customer interactions.

DATA VOLUMES

Data is generated.

Learning from the data is used in the decision making and process optimization.

Data is analyzed.

1.2

2010

2012

2015

2.4

7.9

Volumes in Trillion GB

DID

YOU

KNOW

?

Generation of Large Amount of Data from Business Transactions

4 Billion

Number of transactions every year

900

Number of Stores

Number of SKUs

10000

-1 lakh

Slide9

Why Big Data Analytics?

Why is

Big Data Analytics

important?

Big data analytics helps organizations harness their data and use it to identify new

opportunities. That

, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.

www.imarticus.org

9

Slide10

Enter Data Scientists

Data Scientist:

The

SEXIEST

Job

In The

21

ST

century

Harvard Business Review, Oct 2012

A Business analyst is not able to discover insights from huge sets of data of different domains

.

Data

scientists can work in co-ordination with different verticals of an

organization

and find useful patterns/insights for a company to make tangible business decisions.

INCREASE IN JOB POSTINGS FOR DATA SCIENTISTS IN THE US BETWEEN 2011-12

15,000%

www.imarticus.org

10

Slide11

Demand for Analytics Professionals in India

$ 1 Billion

Jan, 2014

$ 2.3 Billion

Projected for 2018

Analytics Market

$ 163 Million

Jan, 2014

$ 375 Million

Projected for 2018

Domestic Market

31,500

Jan, 2014

2,50,000

Projected for 2018

Job Openings

Source: NASSCOM

Salary Report

Experience

Salary in INR

0-2 Years

4.5 Lakhs

2-5 Years

5.8 Lakhs

5-10 Years

8.8 Lakhs

15 Lakhs

10+ Years

www.imarticus.org

11

Slide12

New Analytics Jobs By Industry

ANALYTICS SERVICES

BANKING

TOTAL NUMBER OF JOBS

PHARMA

Analytics

Services and

Pharma

lead the pack in the highest percentage

of

Analytics jobs being created in developing nations.

US

INSURANCE

OIL & GAS

COMMUNICATIONS TECHNOLOGIES

INDIA

CHINA

UK

BRAZIL

JAPAN

SINGAPORE

11%

14%

39%

20%

14%

2%

38,700

31,500

30,500

7,000

6,200

2,400

1,300

54%

24%

7%

11%

3%

1

%

25%

32%

8%

22%

10%

3

%

9

%

19%

32%

25%

13%

2%

14%

30%

11%

19%

23%

3

%

6%

4

4%

27%

14%

8%

1

%

9

%

26%

24%

25%

9

%

7

%

www.imarticus.org

12

Slide13

Global Clients

And Many More…

www.imarticus.org

13

Slide14

Know Your Tools & Why Learn About Them?

Slide15

Tools Covered in Program

The program is developed keeping in mind the needs of an evolving

Analytics

industry that requires individuals to be “job-ready” from Day 1.

www.imarticus.org

15

Slide16

Why SAS?

T

he

largest independent vendor in the business intelligence market

The

De facto industry standard for Clinical Data Analysis

#

1

Market Leader

in Analytics

Used in 60,000+ companies in over 135 countries

“Analytics powerhouse”

INTEGRATED PLATFORM FOR END TO END SOLUTIONS:

SAS provides an integrated set of software products and services and integrated technologies for information management, advanced analytics and reporting.

Business Solutions across Domains and

Industries:

U

nmatched

domain specific industry focused analytics solutions

The

Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013

16

Slide17

Why R?

R

is the #1 Google Search for Advanced Analytics software

Google Trends, April 2016

Highest Paid IT Skill

Linkedin

Skills and

O'Reilly Survey, 2016

Most-used

data science language after SQL

O’Reilly Survey,

Jan 2014

75%

of data

professionals

use R

Rexer

Survey,

Oct 2015

Second best

programming languages for data science

O'Reilly Survey, 2016

Supports close

to 10,000 free packages

CRAN Figure as on December 2016

R is #13 of all Programming Languages

Redmonk

Language Ratings, June 2015

Demand for R language skills is on the

rise

.

BCG

Uber

Lloyds

of

London& Many More…

Companies Already Onboard R

FacebookGoogleTwitterMcKinseyANZ Bank

www.imarticus.org

17

Slide18

What is

Hadoop

?

Hadoop

is Transforming Businesses Across

Industries

“The

growing use of Apache Hadoop, increasing data warehouse volume sizes and the accumulation of legacy systems in organizations are fostering structured data growth. These factors are leading enterprises to understand how to reuse, repurpose and gain critical insight from this data

.”

Gartner

BIG DATA STORING AND FASTER PROCESSING

Hadoop is an open source software framework created in 2005 that keeps and processes big data in a distributed manner on large collection of hardware.

Organizations

use Hadoop to manage their data

today

(up

from 1 out of 10 in

2012)

1

in

4

Business Solutions across Domains and Industries:Low cost solution with a high fault tolerance to access and create value from data.

www.imarticus.org

18

Slide19

Hadoop – Big Data is a comprehensive class room training program that enables you to analyse data and create useful information for careers in Data Analytics.

Why Hadoop?

Scalability

Computing Power

Top 5 Reasons Organizations are using Hadoop

Low Cost

Storage Flexibility

Data Protection

Top 5 Industries using Hadoop:

Computer Manufacturing

Business Services

Finance

Retail

&

Wholesale

Education

& Government

Enterprises using Hadoop

www.imarticus.org

19

Slide20

Hadoop

& Big-Data Jobs in India

www.imarticus.org

20

Slide21

Why Python?

Cost of Ownership

Python is an open source software that is free to download.

Versatility

Multi-purpose language that can be used to build an entire application

Python is a powerful, flexible, open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis

What are the reasons for its sudden popularity?

A Data Scientists’ Dream

Python

is particularly useful

in data analytics because

it

has a rich library for reading and writing data

, running calculations on the information and creating graphical representations of data sets

.

We can write map reduce programs in python using

PyDoop

. Here is where Python scores over R. While R uses in-memory processing, Python using

PyDoop

can process

PetaBytes

of data

Python offers extensive analytics capabilities for Text & Predictive Analytics.

IDLE &

Spyder

IDE

is

widely used

for data mining.

Big Data Analytics made possible by PyDoop and

Scipy

In industry, the data science trend shows increasing popularity of Python. A Python-based application stack can more easily integrate a data scientist who writes Python code, since that eliminates a key hurdle in

productionizing

a data scientist's work.

Integration

Big data compatibility

Python has become one of the big go-to languages for big data processing due to its wide selection of libraries

www.imarticus.org

21

Slide22

Why Python?

Official language of Google

Among top

in-demand data science skills

KDNuggets

,

Dec2014

46% of job ads mention Python

(after SQL)

KDNuggets

Dec 2014

Ranked #1

of

all

programming languages

Codeeval

rankings

,

Feb 2015

2

nd

most

popular data science language

KDNuggets 2013

Google

Yahoo

QuoraNokia

ABN AMRO Bank

IBMNational Weather Service

& Many More…

Companies Already

Onboard Python

www.imarticus.org

22

Slide23

What is Data Visualization?

Data visualization is the presentation of data in a pictorial or graphical format. For centuries, people have depended on visual representations such as charts and maps to understand information more easily and quickly.

23

Slide24

Why Tableau for Data Visualization?

Cost of Ownership

Tableau is a competitively priced software that is available for a trial download.

Versatility

Multi-purpose package that can be used to build an entire application

Tableau is a powerful, flexible Data Visualization tool that is easy to learn, easy to use, and has powerful libraries for data visualization and presentation.

Big data compatibility

Tableau has become one of the big go-to software programs for Data visualization due to the wide variety of tools it provides and compatibility with Big Data platforms such as Hadoop.

24

Slide25

Why Tableau for Data Visualization?

A Business Analysts’ Dream

Tableau is easy to learn, use, and significantly faster than existing solutions. One can easily see patterns, identify trends and discover visual insights in seconds. No wizards, no scripts.

Tableau facilitates live, up-to-date data analysis that taps into the power of the firm’s data warehouse.

Extract data into Tableau’s data engine and take advantage of breakthrough in-memory architecture.

Tableau offers Powerful visualization capabilities, without a single line of code.

Experiment with trend analyses, regressions, correlations.

Scalable, secure and Reliable Cloud and Mobile Connectivity.

Tableau integrates exceptionally well with R and Hadoop, making it a powerful visualization tool for analytics and big data use cases. Developers creating web applications can integrate fully interactive Tableau content into their applications via the JavaScript API.

Integration

www.imarticus.org

25

Slide26

Careers in Analytics

Slide27

Career Options in Analytics

FIELDS IN ANALYTICS

TARGET AUDIENCE

Data management

Data Exploration

MIS and report creation

Automation of reports

Segmentation

Customer profiling

Portfolio Analysis

Trend Analysis

Forecasting

Probability models

Classification and regression trees

Time series models

Neural networks

Multi-layer Perceptron

Geospatial models

Associative rule learning

Inductive logic programming

INDICATIVE JOB ROLES

KEY FEATURES

No matter what your educational background or aspirations,

you have a fulfilling career in one of the many fields of Business Analytics.

MIS

REPORTING

NON-PREDICTIVE ANALYTICS

PREDICTIVE ANALYTICS

MACHINE LEARNING

BCom

B.E

BTech

MIS Analyst

Data Analyst

Strategy Analyst

Cost Analyst

Data Scientist

Statistician

Advanced Analytics

– Team ManagerMarket / Global Research AnalystAnalytics

Manager

BCom

B.EBTechMBAs B.EBTechMSc (Statistics)MBAsMCAB.E

BTechMSc (Statistics)MBAsMCA

www.imarticus.org

27

Slide28

Career Path and Indicative Salaries (CTC)

Manager

AVP

Senior Analyst

Analyst

Rs. 15-20 Lakhs

Rs. 9-15 Lakhs

Rs

. 6-8 Lakhs

Rs

4-6 Lakhs

Average Salaries

0-2

Yrs

Analyst

2-4

Yrs

Senior Analyst

4-6Yrs

Manager

6-10

Yrs

AVP

CAREER TRAJECTORY

Strong analytical and critical thinking skills

Statistics

Predictive

Analytics

SQL Knowledge

Understanding complex data & tools for Analytics

Soft Skills & Communication

Business

Understanding

Skills require to succeed in the Industry

10-15

Yrs

VP

15+

Yrs

Director

Rs. 15-20 Lakhs

Director

www.imarticus.org

28

Slide29

Careers

Rs. 15-20 Lakhs

Rs. 9-15 Lakhs

Top

Companies

Hiring for

Business

Analytics

www.imarticus.org

29

Slide30

Thank you

Mumbai

| Pune | Bangalore | Delhi - NCR

|

Hyderabad | Chennai

|

Coimbatore

ACCREDITED TRAINING PARTNER:

Contact

info@imarticus.org


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