Introduction to Predictive Analytics and Data collection - 402Introduction to Strategic Data Assets and Tools for Predictive Analytics

Sam - Nethra Sambamoorthi, PhDLead Faculty - 402

Generic slides from this are used in Video 1 – The assignments and dates are examples for WINTER 2014 SECTIONS of MY CLASSES (SEC55,58,63). For

assignment dates for your class, your faculty will provide them

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d. A

naly

tics

and

Dat

a Co

llecti

on

Washington Post article reports…• 65% of the jobs are not yet known that will be normal in 10 years• If not 100% by 10 years, we are moving in the direction of jobs that are

going to be• Digital related• Ubiquitous related• So(power of people – truly democratic) Lo (dynamics) Mo (every person is a

broadcasting station)• Data related• Analytics related• Information products/cooperatives/democratic• All systems in real time

• That will remove inefficiencies in knowledge generation and sharing, remove producer-consumer distance, provide every person their voice, and more and more entrepreneurial aspirations will become easier to accomplish and grow. Innovations supported digital principles and platforms has so much tapped, invented, and integrated in all walks of life…

2

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d. A

naly

tics

and

Dat

a Co

llecti

on

3

The IT sector is likely to need: (more than 50% of titles are related to analytics)information security analysts, big data analysts, artificial intelligence and robotics specialists, applications developers for mobile devices, web developers, database administrators, business intelligence analysts, gamification designers, business/systems analysts and ethicists.In other disciplines, there will be a need for analytics too…engineers of all kinds, accountants, lawyers, financial advisers, project managers, specialist doctors, nurses, pharmacists, physical therapists, veterinarians, psychologists, health services managers, schoolteachers, market research analysts, sales reps and construction workers (particularly bricklayers and carpenters).

IT and CIO offices are going to change

Who

can

pre

dict

?

4

Predictive Sciences and BI Opportunity

• McKinsey estimates that we need globally 150,000 analysts and another 50,000 managers who are talented in analytics by end of 2018

• In April 2012, White House allocated $200MM for Big data initiatives to fund leadership work in Big Data opportunities

• Reference: http://predictive-models.blogspot.com/2013/06/the-famous-mckinsey-study-on-big-data.html

5

The

New

Wor

ld O

ppor

tuni

ty

The BIG Data Opportunity• SAP sponsored BIG data opportunity study by Sand-Hill Group and

Microsoft sponsored BIG data opportunity study by IDC both point to enormous amount of investment and developments in BIG data and commensurate revenue in the next 3-5 years

• $1.1 trillion revenue expected in the next three years due to BIG data

• $40 Billion venture capital money flow and 1.3 million new jobs in the next three years

• Predictive Analytics is also part of this opportunity

6

The

New

Wor

ld O

ppor

tuni

ty

Internet of Things – McKinsey Report• http://

www.mckinsey.com/insights/high_tech_telecoms_internet/the_internet_of_things

• Listen to the 11 minute audio discussion on the opportunities

All,

tool

s, e

quip

men

t, as

sets

, and

inte

racti

ons

are

inte

rcon

nect

ed a

nd re

cord

ed

7

$33 Trillion Technology Payoff by 2025

The

mos

t cer

tain

of a

ll th

ese

is d

ata

inte

llige

nce

and

know

ledg

e w

ork

8

Data, Data, Everywhere

However, you slice and dice, big data and analytics will be at least $250 billion in the next 13 years. Most of which will have to be automated work

Top 10 Concepts, Ideas, Tools1. Meaning of analytics, why it matters, and how different companies are using them (using

case studies)

2. Different stages of analytical competition and how to get your management's attention to lead them to the next level

3. Identifying analytical methods for internal processes and external processes

4. Understanding strategic metrics, and the critical components of bringing out Moneyball phenomenon in your organization

5. Key Performance Indicators and Key Leverage Indicators and the relationship among Strategic metric, KPIs, and KLIs, and how to create an engaging dashboard

6. Building an analytics team and how to integrate it within an organization

7. What is an information strategy and how to create one for your organization

8. Understand data management, data quality, and missing values for analytical processes

9. Four ways of collecting data and how to use sample surveys effectively and understanding how bias needs to be addressed

10. Big data and Big data analytics

Lear

ning

Goa

ls

9

Books and References• Required:• Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Boston, MA:

Harvard Business School. • [ISBN-13: 978-1422103326]

• Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Oakland, Calif.: Analytics Press. [ISBN-13: 978-0970601988]

• Groves, R.M., Fowler, F. Jr., Couper, M.P., Lepkowski, J.M., Singer E., & Tourangeau, R. (2009). Survey methodology (2nd ed.). Hoboken, NJ: Wiley - [ISBN-13: 978-0470465462]

• Gert H. N. Laursen, Jesper Thorlund (2010), Business Analytics for Managers: Taking Business Intelligence Beyond Reporting ISBN: 978-0-470-89061-5

• Recommended

• Thomas Miller (2015), Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science, Pearson Publications, ISBN-13: 978-0-13-389211-6

• Franks, B. (2012). Taming the big data tidal wave: Finding opportunities in huge data streams with advanced analytics. Hoboken, NJ: Wiley. [ISBN-13: 978-1-118-20878-6]

• Siegel, E. (2013). Predictive analytics: The power to predict who will click, buy, lie, or die. Hoboken, NJ: Wiley. [ISBN-13: 978-0470465462]

• Moneyball movie - http://www.moneyball-movie.com/site/ This is available in our course library for free viewing to collect your summary as the first assignment

• My blog: http://blog.crmportals.com/

MSPA - Predict 402 Section 55 - Intro to Pred. Analytics and Data Collection

10

Refe

renc

es a

nd to

ols

Tools, Data Assets, and Analytical Strategies• Understanding strategic metric of an organization and KLI™ (Key

Leverage Indicators) and KPIs (Key Performance Indicators) to leverage daily activities of an organization, using real life story of Moneyball.

• Evaluating maturity levels of organizations on their analytical maturity levels, using Davenport and Harris Model

• Identifying analytical methods for external and internal processes of organizations

• Creating engaging dashboards that connects strategic metrics, KLIs, and KPIs

• Creating a sample survey design proposal, along with a questionnaire, analytical plan, and executive summary

• Third party data sets• APAstyle of document preparation and Microsoft graphical objects

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d.

Anal

ytics

and

Dat

a Co

llecti

on

11

Moneyball Lessons – First Assignment

• (1) what drove the new business model, (2) what strategy was developed in hiring and training under the new approach, (3) how long it took to start seeing the results, (4) what team dynamics started happening between analyst, scouts, and management, and (5) your opinion of whether this real life story bears truth in different industry verticals and whether analytics can help redeem their company.

• Write approximately 3 to 5 sentences for each of the takeaway points and do not write more than 2 pages

• Create the two page summary, use a title page in the spirit of APA style, and name the file as FirstName_LastName_402_WI2014_SECxx_MB.docx

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d.

Anal

ytics

and

Dat

a Co

llecti

on

12

The XX is your section number. For SECTION 55, it is 55, for example.

Submission date: Sunday, 12JAN14, 11: 55 PM

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d. A

naly

tics

and

Dat

a Co

llecti

on

Big Data Review• Review big data and big data analytics videos -

http://blog.crmportals.com/top-videos-on-learning-big-data-science/

• Write a critical summary for a total of maximum of 5 pages. • Create the summary using APAstyle (title, abstract, main body,

conclusion, references), name the file as FirstName_LastName_402_WI2014_SECXX_BD.docx. XX refers to your section number.

• Submit before 19JAN14, 11:55PM CST. 100 points

13

Pred

402

Sec

tion

55 -

Intr

o to

Pre

d. A

naly

tics

and

Dat

a Co

llecti

on

Internal vs. External Analytical Process and Methods

• Select two methodologies and write a maximum of 3 pages on each method. Adding a small example will help clarify the methods and cover the number of pages.

• Create the file using APAstyle, and name the file as FirstName_LastName_402_WI2014_SECXX_IE.docx. XX refers to your section number.

• Submit it before 26JAN14, 11:55PM CST• This is not scored

14

Predictive Analytics Applications and Identifying Case Studies List

• Pick one of the application areas discussed in the book or an industry (vertical) that interests you and identify 5 cases.

For each of the cases (1) profile the company detailing on where it is located, what is their core competency, their products/services (2) how predictive analytics helped. Do not spend a lot of time here. We are trying to get the useful list that interests you.

Demonstrate your ability to draw upon Northwestern University library resources by utilizing relevant peer-reviewed articles from journals like the Harvard Business Review, MIT Sloan Management Journal, and publications from SAS, Oracle, IBM, SAP where success stories are published at their sites. Google "analytics" AND "success stories" AND "IBM", for example, to filter your searches.

Total number of pages expected is around 5 not counting the title, and references. Make sure you include the title, abstract, introduction, main body, conclusion, and references sections.

• The completed document is due before 2FEB14.• This theme and case studies list will be used for the final case studies report. Additional details are

available in the assignment section details of "case studies final" for final paper submission that is due on 2MAR14.

The name of the file to be submitted should be FirstName_LastName_402_WI2014_SECXX_CL.docx (The system accepts only filenames with upto 50 characters). XX is your section number.

The name of the file to be submitted should be FirstName_LastName_402_WI2014_SECxx_CL.docx (The system accepts only filenames with upto 50 characters). 50 Points

Prep

arat

ory

wor

ks fo

r Fin

al C

ase

Stud

ies

List

15

Submission date: Sunday, 2FEB14, 11: 55 PM

Third Assignment – Design a Dashboard

• Use best practices for developing dashboard• One screen, drill-down design, that captures and makes available

the current status (almost in real time) with insights for a number of well understood KPIs/KLIs, and trending customer input on any thing and everything about the company

• This is all about designing the dashboard; so you need some sharp skills in Microsoft graphical objects and graphical outputs as options

• The screen shot design and the executive summary together as one document should be named FirstName_LastName_402_WI2014_SEC60_DB.docx. 100 points.

How

to c

reat

e an

eng

agin

g an

d le

vera

ging

da

shbo

ard

16

Submission date: Sunday, 16FEB14, 11: 55 PM

Final Theme Based Case Studies Submission

• Submit Case Studies Final: Enhancing the previous submissions with insights from MB,BD,IE write ups. Enhance the whole write up on why they are success stories - cite projects, analytical methods, results, and economic impacts

• Depth and width of the discussion is what is expected here whereas in the first stage the attempt is to provide input to organize your thoughts

• This may include interviews of the company executives but references should be provided

• Case Study Collection Final Assignment is due Sunday, 2Mar14, at 11:55 p.m (CST) – 100 Points

• File name should be FirstName_LastName_402_WI2014_SECXX_CF.docx

Mat

urity

leve

l of a

n or

gani

zatio

n in

its

cla

ss o

f ac

tiviti

es

17

Assignment: Survey • Survey Design and Implementation Topic file name should be

FirstName_LastName_402_SU2014_SECxx_ST.docx Due 23FEB14

• This is to get an understanding and input from your lecturer on how to complete your desired topic as a detailed proposal

• The final completed document, prepared in APA style for Survey Design and Implementation should be maximum of 15 pages and the file name should be FirstName_LastName_402_WI2014_SECxx_SF.docx. 150 Points D

evel

opin

g a

Surv

ey D

esig

n an

d Im

plem

enta

tion

18

Submission date for sampling topic: Sunday, 23FEB14, 11: 55 PMSubmission date for final sampling proposal: Sunday, 9MAR14, 11: 55 PM

Discussion Board• The purpose of the discussion boards is to allow students to freely exchange

ideas. • It is imperative to remain respectful of all viewpoints and positions and, when

necessary, agree to respectfully disagree. • While active and frequent participation is encouraged, cluttering a discussion

board with inappropriate, irrelevant, or insignificant material will not earn additional points and may result in receiving less than full credit.

• Frequency is not unimportant, but content of the message is paramount. Please remember to cite all sources—when relevant—in order to avoid plagiarism.

• I will be looking for grammar and sentence construction for direct, active, simple and respectful dialogues for complete scores

• 1 posting stating your position per guiding question is required to get full 10 points, for clarity and content.

• Always provide your view point as a separate start of a discussion for every guiding question posted each week, and provide input to others or post questions to other people’s point of views subsequently.

Etiqu

ettes

of I

nter

actio

n an

d be

nefitti

ng b

y ac

tive

Enga

gem

ent

19

Evaluation of Successful Learning

Evaluation Method

• Big data Review(100 points)• Case Study List (50 pts.)• Sync Session• Dashboard and Executive Summary

(100 pts.)• Case Study Collection Final (100 pts.)• Sync Session• Survey Design and Implementation

(150 pts.)• Discussion Board Participation (100

pts., 10 pts. per session)

• Total Points: 600 pts.

Grading Scale

• A = 93%–100%

• A- = 90%–92.9%

• B+ = 87%–89.9%

• B = 83%–86.9%

• B- = 80%–82.9%

• C+ = 77%–79.9%

• C = 73%–76.9%

• C- = 70%–72.9%

• F = 0%–69.9%

Gra

ding

Met

hod

20

Attendance and Participation• This course will not meet at a particular time each week.• All course goals, session learning objectives, and assessments

are supported through classroom elements that can be accessed at any time.

• To measure class participation (or attendance), your participation in threaded discussion boards is required, graded, and paramount to your success in this class.

• Please note that any scheduled synchronous or “live” meetings are considered supplemental and optional. While your attendance is highly encouraged, it is not required and you will not be graded on your attendance or participation.

21

Late Work• Unless otherwise noted, all work is due on the assigned day by

11:55 p.m. (central time). This includes exams and participation in the discussions. Late work is not accepted.

• One more piece of advice—do not fall behind. We cover a lot of material in this course, and falling behind is the primary reason why folks fail. To that end, you have below the due dates for the entire course. It is much, much better to be ahead than behind.

22

Discussion Board Evaluations

• Respond to you with in 48 hours in email; most of the times with in 24 hours• A large of collection of office hours• While I will read every one of your comments and responses in discussion

boards, to let your creativity in articulation, discussion, and interpretation, I will respond to specific question posted to me either directly in a personal email or in the discussion board, or when I see there are confusing or inconsistent statements are posted in the discussions that do not get any one else’s response

• Post evaluations of discussions before the following Sunday• Make every effort to provide you an expanded and critical evaluation needed

for this course that would help you right away in your daily, organizational, and professional work.

• I value your input from you all and it is my honor to expand the horizons of your vistas in management of predictive analytics opportunities in concepts, areas of applications, and data assets

23

Utilizing Library FacilitiesMs. Qiana Johnson - Librarian

• Qiana Johnson is the Distance Learning Librarian at the Northwestern University Libraries and the liaison to the School of Continuing Studies. She has presented and published in a number of areas including working with nontraditional graduate students and library collections. At the end of tonight’s session, students will be able to locate articles about companies and their strengths and/or weaknesses in their use of analytics using library resources.

Listen to this pre-recorded version of her presentation. If the link does not work, use the following to copy and paste in a newly opened browser - http://nwuniversity.adobeconnect.com/p5mg1vo1zdi/

• Students are encouraged to contact Qiana at 312.503.6617, q-johnson@northwestern.edu, or through the IM widget at the Predictive Analytics Research Guide page, http://libguides.northwestern.edu/predictiveanalytics.

24