Overview of the landscape of roles within the field of Business Intelligence

Distinction between different roles with respect to their focus on Description, Diagnosis, Prediction, and Prescription

Tools and skill-sets that might be required to qualify for these roles

Trends and growth opportunities associated with each role

1. Professional, Scientific & Technical Services​

2. Information​ Management

3. Manufacturing 

4. Retail Trade

5. Waste Management

6. Finance & Insurance

27%

19%

12%

10%

8%

8%

Wanted Analytics via Forbes, 2014

BI Team Manager

BI Consultant

Visual Analytics Specialist

Data Scientist

OR Scientist

description

diagnosis

Prediction

Prescription

Role Description:

Provide clients with services and advisory based on industry best practices and domain experience in order to conduct assessments, develop strategies, and implement solutions related to:

Enterprise Information/Data Management Architecture 

Enterprise Data Warehouses and Datamarts

Analytics and reporting solutions

Skillsets:

Deep experience in a particular software package, domain/industry, and/or methodology

Example Toolsets:

• Large firms: Commercial analytics platforms,                                  e.g. SAS, Oracle BI, IBM, Teradata, Tableau, etc.
• Small firms: Open source software,                                                    e.g. R Studio, Hadoop, Weka, GAMS, Jaspersoft, etc.

Strong communication and change management skills

Skillsets exceeding or matching those expected of your level in the client organization

Trends & Growth Potential:

Very hot market right now with companies trying to quickly hop onto the "Big Data Bandwagon".

Other companies with more analytics maturity are electing to build their own self-sufficient analytics teams without outside help.

Role Description:

Provide for...

Team Leadership

Communications

Quality Assurance

Management Needs

Project Management

Ensure efforts remain aligned

 with stakeholder interest and/or business objective.

Skillsets:

• Ability to lead high-performing individuals and leverage their skills effectively
• Strong communication skills; fluency in both business-speak and tech-speak
• Agile project management experience
• Analytical background complemented with business & leadership experience

Example Toolsets:

• Typical tools used by managers in IT settings
• In smaller teams, may need some experience with the tools used by the team

Trends & Growth Potential:

There is a high demand for people with balanced technical and business skillsets to fill this role

interactive & innovative complex data visualizations

Create

Role Description:

Build

analytics ecosystems to help make better business decisions, faster

Distribute

dashboards and data visualization projects that provide insight to drive business decisions

Skillsets:

Excellent communication skills and strong teamwork skills

Example Toolsets:

Business Intelligence experience and Tableau Desktop experience

Capable of presenting numerical findings in a visual format easily understood by business

Trends & Growth Potential:

Huge growth in Big Data, both structured and unstructured, drives the great need of this role

Business Leaders need the insights presented in simple visual formats that aid and speed decision making

Role Description:

Data Scientist

Data Analyst

Clean, organize, structure data, create data models, analyze for trends

Data Mining

Innovation

Predictive Modeling

Develop predictive models for to maximize efficiency

Make recommendations to improve ROI and come up with innovative ideas

Skillsets:

Example Toolsets:

• Proficiency with some of the following analytical tools,                                   e.g. Python, SAS, R, SPSS Tableau, Spotfire, D3, SQL, Scala, Java. etc.    

Able to work in dynamic team environment & manage communication with multiple stakeholders

Trends & Growth Potential:

The global management firm McKinsey & Company recently reported that by 2018 there will be a shortage of 140,000 to 190,000 data scientists. This represents a 50 to 60% talent gap to meet projected demands.

"Sexiest job of the 21st century"

"Data scientist today are akin to Wall Street "Quants" of the 1980s and 1990s."

          - Harvard Business Review

Role Description:

• Identify and define business problems, such as those in: 

production 

logistics

sales

• Examine data to figure out what is relevant to the problem

DISCOVER

Optimize assembly line performance

Minimize inventory level

Maximize profit

Skillsets:

Communication skills

Critical-thinking skills 

Communicate technical information to people who do not have a technical background.

Figure out what information is relevant to work; evaluate the costs and benefits of alternative solutions before making a recommendation.

Ingenuity 

Think creatively to solve problems.

Diagnose problems on the basis of information given to them by others; analyze relevant information to solve the problems.

Problem-solving skills

Use models and methods rooted in statistics, calculus, linear algebra, and other advanced mathematical disciplines.

Math skills

Report findings & recommendations.

Writing skills

Interpersonal skills

Team player.

Example Toolsets:

Simulation softwares, and Optimization softwares,                               e.g.  R, GAMs, LINDO, Simio, Excel, etc.

Trends & Growth Potential:

About 73,200 jobs in NA in 2012; Demand Should continue to grow

- US Bureau of Labour Statistics

Employment is projected to "grow by 27% from 2012 to 2022", "much faster than the average of all occupations

- US Bureau of Labour Statistics

VS.

VS.

$600 Billion

potential annual consumer surplus from using personal location data globally

60% 

potential increase in retailers' operating margins

14,000-19,000

more deep analytical talents needed

1.5 Million

more data-savy managers need to take full advantage of big data in the US

McKinsey Global Institution, 2011