Tools for Building a Big Data Career Pathway

Joyce Malyn-Smith, Principal InvestigatorEducation Development Center/ Oceans of Data Institute

John Hamman, Dean of Mathematics, Statistics and Data ScienceMontgomery College, MD

2018 Data & Analytics SummitSeptember 7, 2018ColIege Park, MD

EDC

EDC creates learning opportunities for people around the world, empowering them to pursue healthier, more productive lives.

Oceans of Data Institute

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Tools for Building a Big Data Career Pathway

• Profile of a Data Practitioner

• Rubrics

• Building Blocks for a Big Data Career Pathway

• Gap Analysis Tool– Industry Industry Importance

– School Capability

• Heat Map

4Copyright © 2016 by Education Development Center, Inc. All rights reserved.

Building the Foundational SkillsNeeded for Success in Work at

the Human-Technology FrontierJoyce Malyn-Smith, Ed.D. David Blustein, Ph.D. Sarita Pillai, M.B.A. Caroline E. Parker, Ed.D. Ellen Gutowski, M.A.

A. J. Diamonti, M.A.

stelarSTEM Learning and Research Center

The Growing Need for Data/ Big Data Skills

“I’ll pause for a moment so you can let this information sink in.”

– By 2018, there will be 4 million big data-related positions in the United States that require quantitative and analytical skills, but a shortfall of 1.5 million data-savvy managers and analysts to fill them. (McKinsey Global Institute)

– The job market for various data analyst disciplines is growing at an annual rate of 27%. (U.S. Bureau of Labor Statistics)

Pathways to Data Careers

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Career Pathway:

a “well-articulated sequence of quality education and training offerings and supportive services that enable educationally underprepared youth and adults to advance over time to successively higher levels of education and employment in a given industry sector or occupation.” (Center for Postsecondary and Economic Success, 2013)

Creating Pathways for Big Data Careers

Laying a Foundation

• Listen to employers to know what to teach– Define occupations critical to the pathway– Identify skills, knowledge and behaviors expected of workers– Develop assessment frameworks

Developing an Occupational Profile

What are the skills, knowledge and behaviors of a

“Big Data Enabled Specialist”?

BiotechnologyMarine Science

Financial ServicesMedical Device Manufacturing

Law Enforcement/ForensicsAgriculture

Public Policy

Education/ Non-Profit

Business Consulting

Health Care

Characteristics Guiding Profile Development

• Informed by Expertise

• Diversity of Perspectives

• Grounded in Specificity

• Defined by Consensus

• Wide Acceptance

Copyright © 2017 by Education Development Center, Inc. All rights reserved. 12

What are the skills, knowledge and behaviors of a “big data-enabled specialist”?

Skills: Analytical Thinking (96%)

Critical Thinking (84%)

Problem-solving (75%)

Applying Statistical Methods (74%)

Data Manipulation (70%)

Knowledge: Analytic Thinking (89%)

Algorithms (e.g., machine learning, statistics) (76%)

Data Modeling (70%)

Data Structures (70%)

Best Practices (69%)

Statistics (69%)Behaviors: • A problem solver (89%)• A lifelong learner (78%)• Willing to question (78%)• A seeker of patterns (67%)• Open-minded (67%)

As identified by an expert panel of big data users, and verified by nearly 200 big data users:

How do Educators use Occupational Profiles?

• Develop curriculum and programs• Develop articulation agreements• Develop assessments• Strengthen relationship with employers

– Assess employers’ skill needs – Promote discussion on employer input into curriculum– Conduct a gap analysis to determine if curriculum is

aligned with local employer needs• Help students organize portfolios, develop resumes and

prepare for interviews

Profiles Developed

• Big Data Enabled Specialist• Data Practitioner• Social Technology Professional• Technology-Enabled Investigator• Employment Specialist• Computational Thinking Research Scientist• Computational Thinking Product Engineer• Computational Thinking Integration Specialist

Beyond the Profiles

• Performance based rubrics

• Skills gap analyses

• Problem based curriculum

NSF-ATE Creating Big Data Career PathwaysBuilding Blocks for a Big Data Career Pathway

Please provide the following information regarding the programs, certificates and courses that relate to your school’s development of a big data career pathway.

Your School ________________________________ Person Completing Form ______________________________

Name of Program Indicate if –In place (X) orPlanned (P), (with projected start date.)

Names of courses and course numbers

Prerequisites Necessary for Enrollment

Name(s) of Jobs Program Prepares Graduates For

Names of CompaniesActively Supportive of Program

Two Year Programs

Name of Certificate Indicate if –In place (X) orPlanned (P), (with projected start date.)

Names of Courses Included and course numbers

Prerequisites Necessary for Enrollment

Name(s) of Jobs Certificate Prepares Graduates For

Names of Companies Actively Supportive of Certificate

One Year Certificates

Name of Course Indicate if –In place (X) orPlanned (P), (with Projected start date.)

Name of Program/ Certificate Brief Description Number of Credits

Courses in Your School’s Pathway

Name of relevant Courses or Activity (e.g. internship) How does this relate to other components of your career pathway?

Names of Companies Actively Supportive of Course or Activity

Other courses and/ or activities not included above that relate to your school’s big data career pathway.

Name of Program/ Certificate Name of Four Year college that has articulation agreement with your school

Brief description of agreement Is agreement already in place or in the planning stage?

Identify Four Year Colleges that Your School has an Articulation Agreement with related to the program(s) and certificate(s) identified above.

Name of Employer Contact Person Contact Information

Contact Information for Employers Supportive of Your School’s Big Data Career Pathway

Employers Supporting (Name of School’s) Big Data Career Pathway

Please indicate all actions you and/ or your company are willing to take to support (Name of School’s) Big Data Career Pathway.

Name ____________________________________________

Position ___________________________ Company _______________________________

Telephone _________________________ E-Mail _________________________________

Supportive Action Yes! Maybe, more discussion needed

No

Provide input into curriculum development

Provide guest speakers for data courses

Host field trips by students enrolled in data courses

Allow students to “shadow” data workers

Offer unpaid internships

Offer paid internships

Conduct mock job interviews

Participate in college sponsored career days

Serve on Industry Advisory Committee

Provide labor market data, e.g. info about job openings

Support fundraising efforts to strengthen the pathway

Other?

Other?

Mapping employer expectations

INITIATES THE PROJECT

SOURCES THE DATA

TRANSFORMS THE DATA

ANALYZES THE DATA

1.

2.

3.

4.

CLOSES OUT THE PROJECT5.

ENGAGES IN PROFESSIONAL DEVELOPMENT

6.

1A. Translates business problems into analytic needs.

2

1B. Interviews stakeholders

4.

1C. Refines stakeholder needs.

2

1D. Identifies appropriate data.

7

1E. Identifies whether data exists or not.

8

1F. Performs gap analysis of the data.

9

1G. Determines resource needs (e.g., SMEs, tools, timelines).4

1H. Determines feasibility of analysis to be done.3

1I. Creates statement of work.

4

2A. Determines data source(s).

5

2B. Determines target structure.

4

2C. Collects data.

10

2D. Exercises quality control (e.g., randomizes selection).7

2E. Extracts data (e.g., writes SQL, API code).8

2F. Cleans data (e.g., identifies outliers/errors).9

2G. Tests data.

9

2H. Creates data dictionary.

5

2I. Complies with business, ethical and legal standards.8

3A. Merges data.

9

3B. Splits data.

9

3C. Derives new variables.

5

3D. Creates new data.

4

3E. Augments data.

5

3F. Applies meta-data.

6

3G. Purges data.

4

3H. Changes data structure.3

3I. Changes data types.5

3J. Normalizes data.8

3K. Interpolates data.5

3L. Finalizes data dictionary.4

3M. Stores data for analytics.6

4A. Determines what analysis to run.

2

4B. Applies the research method and tools.

6

4C. Identifies dependent and independent variables.5

4D. Defines appropriate algorithms.

3

4E. Performs data mining.

7

4F. Separates any anomalies.

5

4G. Interprets the results.

4

4H. Runs additional tests as needed.

5

4I. Performs reasonableness tests of results.

2

4J. Compares results to previous findings.

5

4K. Confirms results.

5

4L. Conducts causality testing.

5

4M. Creates data visualizations (e.g., dashboards, reports, charts, graphs, videos, animation).9

5A. Selects documentation media.

6

5B. Describes problem, method and analysis.

6

5C. Articulates conclusions.

4

5D. Compiles reports.

8

5E. Presents information to stakeholders.

4

5F. Integrates feedback from stakeholders.

4

5G. Defends analysis as needed.

3

5H. Reworks analysis as needed.

6

5I. Prepares final report.

5

5J. Archives work products.

8

5K. Communicates future processes, improvements and opportunities. 3

6A. Maintains professional qualifications.

6

6B. Stays current on emerging technologies, methods and tools.

8

6C. Seeks out mentors.

10

6D. Shares best practices.

7

6E. Contributes new knowledge to the field.

5

6F. Attends relevant conferences and seminars.

6

6G. Mentors others.

1

6H. Participates in professional organizations.

7

6I. Suggests future projects.

5

Tasks

Learning Occupation: The Data Practitioner, in service of an organization and/or stakeholders, supports the data life cycle by collecting, transforming, and analyzing data, and communicating results in order to inform and guide decision-making.

Duties

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All rights reserved.

Identifying current focus of curriculum

GAP

Work Task IndustryImportance

GAP CollegeCapacity

4A. Determines what analysis to run. 1 2 3

4E. Performs data mining. 2 0 2

4M. Creates data visualizations (e.g., dashboards, reports, charts, graphs, videos, animation).

3 2 1

5D. Compiles reports. 3 1 2

Interpretation of GAPS

0 = Our college is meeting industry’s need for this skill or knowledge set.Adjustments to our curriculum are not needed.

1 = Our college and local industry have similar views on this job function and/or performance activity. Curriculum adjustments may not be needed.

2 = Our college and local industry view this job function and/or performance activity differently. We need to discuss this with local industry partners and determine what curriculum adjustments might be needed.

3 = Our college is not meeting industry needs related to this job function and/or performance activity. Consideration needs to be given to the job function and/or work activity and whether it should be added or removed from the curriculum. Dialogue needs to be initiated with industry partners to discuss this skill or knowledge set.

Johnson County CC -

• Data Science Certificate (Fall 2017) with the following new courses:– Intro to Data Science (Fall 2017)– Data Visualization (Fall 2017)– SQL for Data Analysis (Fall 2017)– Intro to Statistical Programming (Fall 2017)– Data Analysis (Fall 2017)– Data Mining (Fall 2017)– Intro to Machine Learning (Fall 2017)– Big Data Architecture (Fall 2017)

Sinclair CC

• Domain Specific Data Programs Currently Offered:– Health Analytics– Digital Marketing

• Domain Specific Big Data Program added Fall 2017– Data and Information Management – 18 credits

• Intro to Software Applications• Spreadsheet Software• Data Management and Visualization (new course)• Database Software• Business Math• Foundations in Business

Normandale CC

• Associates degree in Data Science (Fall 2017)

• One year certificates in– Analytical Statistics (Fall 2017)– Computational Analytics (Fall 2018)– Data Visualization/Presentation (Fall 2018)

• New courses:– Introduction to Data Science (Spring 2018-19)– Statistical Modeling (Spring 2018-19)

Bunker Hill CC

• Stackable Credentials leading to a 62 credit AS degree in Big Data– Data Management Certificate (1st level)– Data Analysis Certificate (2nd lwvwl)– EMC DSA Certificate (data science associate)– VCA & VCP Certificate (VMware certified associate &

professional)– EMC ISM Certificate (information storage and management)– As AS degree in Big Data

MC Montgomery College – Make Your Move

About MC . . .

On September 16, 1946, the first Montgomery College classes were held in the evenings at an area high school with a student body of 186 men and women.

Today, the College has multiple campuses and serves nearly 60,000 credit and non-credit students from over 160 countries

The county's 202 public schools serve more than 148,000 students with over 20,000 employees. Largest school system in Maryland and 17th largest in U.S.

MONTGOMERY COLLEGE – Data Science

Are you interested in an in-demand field that helps people make better decisions through data?

How do smart choices and innovations in the collection and analysis of data help improve delivery of service, weather forecasting, or a company’s bottom line? How do government, science, and industrymake decisions using data to serve constituents, consumers, patients, and all of society?

These fields are looking for people with analytical and communication skills and training – people who will help them get results!

Our NEW program offers a comprehensive educational experience in this rewarding field.

Key Questions While Creating a Program

• The pathway for students – where will students go?

• The pathway for faculty – who will teach these courses?

• Credit/workforce distinctions – what does a student need?

Have a plan to periodically revisit these questions.

The MC Data Science Pathway

Data, But Verify: How Montgomery College Used Job Postings & Employer Conversations to Develop Data

Science Program

Job Market Analysis

Faculty Credentials

What are the skills, knowledge and behaviors of a “big data-enabled specialist”?

Skills: Analytical Thinking (96%)

Critical Thinking (84%)

Problem-solving (75%)

Applying Statistical Methods (74%)

Data Manipulation (70%)

Knowledge: Analytic Thinking (89%)

Algorithms (e.g., machine learning, statistics) (76%)

Data Modeling (70%)

Data Structures (70%)

Best Practices (69%)

Statistics (69%)Behaviors: • A problem solver (89%)• A lifelong learner (78%)• Willing to question (78%)• A seeker of patterns (67%)• Open-minded (67%)

As identified by an expert panel of big data users, and verified by nearly 200 big data users:

Workforce/Credit Connections

Questions?

Contact Information

For more information about the DATA Profiles or other profiles of emerging skill sets contact:

Joyce Malyn-SmithPrincipal Investigatorjmalynsmith@edc.org

Joe IppolitoProject Directorjippolito@edc.org