Big Data and Analytics - Why Should We Care?

Big Data & Analytics – So What?

A few answers by Vishwa Kolla

(Prepared for UMass Boston MBA Students)

April 10, 2023Big Data & Analytics - Why Should We Care? 2

About Vishwa Kolla

Vishwa Kolla | [email protected]

Vishwa KollaSr. Consultant, Advanced Analytics & ModelingDeloitte Consulting, Boston

MBA Carnegie Mellon UniversityMS University of DenverBS BITS Pilani, India

Professional Interests Absolutely love solving a variety of business

problems using advanced, predictive analytical techniques and building decision support systems as a means

My engagements typically involve synthesizing Big Data into actionable insights

Some engagements include: Helping F5 firm solve customer attrition Helping Top 5 professional services firm solve

employee attrition Predicting what will viewers watch and when on

TV for a large Cable company Building demand forecast models Implementing scoring engines & building

simulators

Personal Interests Most recent interest - watching my 4 year old

grow (lot of fun and lot of work) Volunteering for a non-profit organization to help

it grow and shape the direction of its growth Outdoor activities – climbing 14ers (peaks over

14,000 ft. high), skiing Traveling Meeting new people Philosophy – understanding differences between

cultures and reasons why various cultures developed and are as they are currently

Coaching / Mentoring / Teaching / Helping people reach their highest potential

Big Data & Analytics - Why Should We Care? 3

Contents

April 10, 2023

What is Big Data?

Why is Big Data Important?

How does Big Data manifest in our daily lives?

Who is into Big Data?

What skills are required to master Big Data?

How can I get started?


What is Big Data?

Source(s): (1) Gartner

Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

- Gartner

http://www.gartner.com/it-glossary/big-data/


What is Big Data?

Source(s): (1) IBM’s Understanding Big Data eBook (2) Intel’s Big Data 101, (3) The Big Data Group (4) YouTube Press statistics

Dawn oftime

2003 2012

5 EB

…

2.7 ZB

2015

10 ZB (E)

Volume of data created Worldwide

1 YB = 10^24 Bytes 1 ZB = 10^21 Bytes 1 EB = 10^18 Bytes 1 PB = 10^15 Bytes 1TB = 10^12 Bytes 1 GB = 10^9 Bytes

Variety of data

Velocity of data

Walmart handles 1M transactions per hour Google processes 24PB of data per day AT&T transfers 30 PB of data per day 90 trillion emails are sent per year World of Warcraft uses 1.3 PB of storage

Facebook when had a user base of 900 M users, had 25 PB of compressed data

400M tweets per day in June ’12 72 hours of video is uploaded to Youtube

every minute

Radio TV News E-Mails Facebook

Posts

Tweets Blogs Photos Videos (user

and paid) RSS feeds

Wikipedia GPS data RFID POS

Scanners …

Volume

Variety

Velocity

Big Data Elements


How Big is Big, Really?

Source(s): (1) Mozy.com


Big Data & Analytics Ecosystem – It revolves around improving people’s lives

Data Providers (Instrumented & Non-instrumented)

Data Store (Structured & Unstructured)

1Data is generated from a wide variety of sources that are either Instrumented (e.g. POS scanners, Video surveillance cameras) Non-Instrumented (e.g., Facebook posts, Twitter feeds, blogs)

The format of the data is either Structured (e.g. database tables) Un-structured (e.g., E-Mails, Blogs, Photos, Videos)

2

3 Visualization &Analytics

Apps & Devices

4

People

5

Visualization tools are used to better understand inherent patterns The data is processed, transformed and analyzed to create insights More often than not, scoring models are built that auto-generate insights

Desktop / Web / Mobile apps consume these insights E.g., Desktop -> Dashboards, Web -> Movie recommendations, Mobile

(Restaurant recommendations)

Improving people’s lives is almost always the end goal The uses of big data and analytics transcends industries, firms and functions


Contents

April 10, 2023

What is Big Data?







It is not about having a lot of data; it is about USING data effectively

Source(s): Google finance

Value gap as perceived by the market. Effective use of big data amongst other things is an important driver of this gap


It is not really about Big Data, but is really about Tiny Data (i.e, INSIGHTS)

Who will this customer watch?

Who is likely to attrite?

Who is likely to respond to an offer?

What should I offer?

What is similar to this customer?

Who should I hire?

What will demand be in 2014?

What does this customer value?

How much should I spend on marketing?

How much stock should I carry?

Given weather patterns, what should I sell?

Which ad will this customer

watch?

What is at the risk of default?

Who is likely to vote for the

democrats?


Contents

April 10, 2023

What is Big Data?







Then and Now – Marketing

Source(s): (1) Big Data Trends by David Feinleib

Then Now

Marketing Leads Campaign Recommendations


Then and Now – Selling


Then Now

One size fits all Personalization & Targeted Selling


Then and Now – IT


Then Now

Peruse through log files Interactive Dashboards


Then and Now – Customer Service


Then Now

Reactive Customer Service Pro-active Customer Service


Then and Now – Credibility


Then Now

Credit Databases Professional & Social Networks


Then and Now – Operations


Then Now

Maps Location Based Services


Then and Now – Medical Research


Then Now

Keyword searches Word Clouds


Then and Now – Fitness


Then Now

Manual tracking Focus on the goal


Contents

April 10, 2023

What is Big Data?







The Big Data buzz has begun; every one is into it …

WSJ• Teaming up on Big Data• Re-inventing society in the wake of Big Data• Wanted – A few good data scientists• Big Data adds nickels and dimes to Giant Wind Farm• Visa uses Big Data in Fraud detection• How Big Data is changing the Whole Equation of Busine

ss• Moneyball, VC Style (using Big Data)• Big Data, Big Blunders• The New Shape of Big Data• What your CEO is reading – Steam Engines Meet Big D

ata

A few company sites about Big Data• Deloitte’s Big Data site• PWC’s Big Data site• IBM’s Big Data site• Intel’s Big Data site• Microsoft’s Big Data site• Walmart

Books / Articles• IBM’s E-Book• Deloitte E-Book• HBR – The management revolution• HBR – Making Advanced Analytics work for you• HBR – Next best offer• Amazon books

Big Data in Various Industries• Healthcare• Financial Services• Big Data in Insurance• Retail

Big Data in Various Functions• Marketing• Operations• HR• Finance

http://deloitte.wsj.com/cio/2013/03/25/teaming-up-on-big-data/?KEYWORDS=big+data

http://blogs.wsj.com/cio/2013/03/22/reinventing-society-in-the-wake-of-big-data/?KEYWORDS=big+data

http://deloitte.wsj.com/cio/2013/03/13/wanted-a-few-good-data-scientists/?KEYWORDS=big+data

http://blogs.wsj.com/cio/2013/03/12/big-data-adds-nickles-and-dimes-to-giant-wind-farm/?KEYWORDS=big+data

http://blogs.wsj.com/cio/2013/03/11/visa-says-big-data-identifies-billions-of-dollars-in-fraud/?KEYWORDS=big+data

http://online.wsj.com/article/SB10001424127887324178904578340071261396666.html?KEYWORDS=big+data






http://blogs.wsj.com/cio/2013/03/08/what-your-ceo-is-reading-steam-engines-meet-big-data/?KEYWORDS=big+data

http://blogs.wsj.com/cio/2013/03/08/what-your-ceo-is-reading-steam-engines-meet-big-data/?KEYWORDS=big+data

http://www.deloitte.com/view/en_US/us/Services/additional-services/deloitte-analytics-service/603d2e86f4755310VgnVCM1000001a56f00aRCRD.htm

http://www.deloitte.com/view/en_US/us/Services/additional-services/deloitte-analytics-service/603d2e86f4755310VgnVCM1000001a56f00aRCRD.htm

http://www.pwc.com/us/en/increasing-it-effectiveness/big-data.jhtml

http://www-01.ibm.com/software/data/bigdata/

http://www.intel.com/content/www/us/en/big-data/big-data-analytics-turning-big-data-into-intelligence.html

http://www.microsoft.com/en-us/sqlserver/solutions-technologies/business-intelligence/big-data.aspx

http://smartdatacollective.com/bigdatastartups/111681/walmart-makes-big-data-part-its-social-media

https://www.ibm.com/services/forms/signup.do?source=sw-infomgt&S_PKG=ov8257&S_TACT=109HF53W&S_CMP=is_bdebook3

http://www.deloitte.com/view/en_US/us/Services/additional-services/deloitte-analytics-service/insight-economy/index.htm?id=us_google_bigdata_102612&gclid=CKi8zYCAmrYCFYbc4AodwGMA6w

http://hbr.org/2012/10/big-data-the-management-revolution

http://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1

http://hbr.org/2011/12/know-what-your-customers-want-before-they-do/

http://www.amazon.com/s/ref=nb_sb_noss_1?url=search-alias=aps&field-keywords=big%20data&sprefix=big+d,aps&rh=i:aps,k:big%20data

http://www.cccblog.org/2013/01/30/big-data-and-healthcare-infographic/

http://www.bigdatafs.com/

http://www.informationweek.in/bfsi/13-01-15/big_data_bigger_opportunities_for_insurance_companies.aspx?page=2

http://www.bigdataretailforum.com/

http://www.toprankblog.com/2012/08/big-data-what-marketers-need-to-know/

https://www.informs.org/About-INFORMS/News-Room/O.R.-Analytics-at-Work-Blog/Operations-Research-Big-Data-to-Tie-Knot-in-April

https://www.bersin.com/blog/post.aspx?id=574b5527-ce55-4ec6-8c45-c8f05f85162e

http://www.bigdataforfinance.com/


… and they are into it very seriously


Contents

April 10, 2023

What is Big Data?







Skills Required to Master Big Data

Data Providers (Instrumented & Non-instrumented)

Data Store (Structured & Unstructured)

1 Hardware engineering Instrumentation & Design Content generators (FB posts, blogs, videos, photos)

Cloud RDBMS (SQL) NoSQL, Hadoop

2

3 Visualization &Analytics

Apps & Devices

4

People

5

Effective Data visualization techniques Statistical & Probabilistic techniques Analytical methods, tools & processes

Web 2.0 Mobile Apps Device specific - iOS / Andriod Device agnostic – HTML 5.0

Leadership Management Administrative Consulting People


Skills Required to Master Big Data & Analytics

Statistical &ProbabilisticTechniques

VisualizationTechniques

Programming & Trouble-shooting

Genuine Curiosity

Industries

Functions

Customer Analytics Profitable growth

opportunities Next best offer Cross-Sell

Fraud Analytics Fraudulent claims Fraudulent transactions

Marketing Analytics Pricing Price & demand

optimization Market Mix

Lifestyle & Life Stage Insurance Premium Pricing Detecting diseases based on

lifestyle

Workforce Analytics Hiring Growing Retaining

Subscription Analytics Credit Score Analytics in the cloud


Skills Required to Master Big Data & Analytics – Some Tools to Learn

Source(s): http://www.bigdatalandscape.com/

http://www.bigdatalandscape.com/


Skills Required to Master Big Data – Example 1 of effective visualization


Skills Required to Master Big Data – Example 2 of effective visualization

Source(s): Visual News

http://www.visualnews.com/2012/09/27/vintage-infographic-napoleons-disasterous-russian-campaign/


Contents

April 10, 2023

What is Big Data?







Navigating Big Data and Analytics is a Journey

Foundation(School)

Learn from the experts

Grow

EstablishMaster ofBig Data

& Analytics

1. Develop your eminence (by publishing your work)

1. Solve the same problem across industries

2. Solve different problems across industries

3. Apply methods across functions

1. Pay attention in Probability & Statistics courses2. Learn at least one programming language thoroughly and a few if

you can 3. Recommended minimum tool sets: R, SAS, Tableau4. Take advanced level analytical courses such as New Product

Introduction, Optimizations, Operations Research, Data-mining, Modeling, Forecasting & Time Series, Simulations

5. Practice solving problems end-to-end to understand the implication of building models and implementing them in real life

1. Learn industry best practices when you get hired into a firm

2. Surround yourself with good people and experts to accelerate your learning

3. Build / implement models under the guidance of an expert


Some things to watch out for

1. Big Data is not a panacea

2. Big Data is not everything for everybody

3. Big Data does not have all the answers and is directional at best if done right

4. Big Data & Analytics do not replace human intelligence ; Relying solely on Data & Analytics usually trips one up

5. There are several limitations of using Big Data & Analytics. Some are:

a) Data collection limitation -> Not all data can and is collected. One may have access to a ton of data, but very little can be analyzed and/or is meaningful

b) Data quality limitation -> Garbage in garbage out; this is getting better every day

c) Data transformation limitations -> Raw data is rarely used. It is almost always transformed. There is no perfect transformation

d) Measurement limitation -> Metrics cannot capture the entire picture

e) Modeling limitation -> Not every relationship can be modeled. The models mostly confirm / deny hypotheses. Again, models need to be evaluated for their predictive strength before adoption

f) Interpretation limitation -> One needs to be careful when interpreting results and often misinterpretations of data / metrics / model insights can be dangerous

g) Actionability limitation -> Not all insights are actionable. They may very well be interesting, but one cannot act on most insights

h) Using / Relying on single data source / data point -> Coming to a conclusion based on a single or very few biased data points can often happen

6. At the end of the day, to make Big Data & Analytics work for you, one needs to question the outcomes and insights, reconcile with understanding and use the insights as illumination as opposed to for support


Summary

1. Big Data is Big. It is easy to get lost. Know and understand what you are getting into before you leap

2. Make up your mind of where you want to play (i.e., get into the area where your strengths lie)

3. Build a roadmap of where you want to go and how you are going to get there

4. Fill in the skill gaps

5. Surround yourself with good people. You are a sum total of who and what you interact with

6. Have fun and enjoy what you are doing


Questions?

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