Analytics for Team Leads: Optimize Analytics & Data Science for More Efficient Operations and Engaged Employees

Join DMAIPH and Augment BPO in a two-day analytics training for Team Leads on August 22-23, 2017 in Ortigas!

Learning Session Description

Every organization is looking for a way to better understand what’s working and what’s not working in their operations. By using meaningful Big Data Analytics techniques, your leadership efforts can be greatly enhanced.

Learning Session Outline

In the past few years, we have seen the importance of big data, analytics and data science grow at a dizzying pace.

With real-time operations metrics & reporting, we can finally know what’s happening in our business, with our employees and with our customers.

New technologies like social networks, data rich information systems and business intelligence applications are fundamentally changing the entire operations process.

The pressure to deliver results has never been greater. Team Leaders are now more than ever required to demonstrate the return on investment of their efforts are contributing to the bottom line.

Building analytics centric teams and using techniques taught in this training session will empower more data-driven decision making. This will result in both process efficiency and better return in investment in the operations of your business.

With the global demand for analytics-enabled talent booming and the coming threat of A.I. to the BPO industry, Team Leaders need a deep understanding of analytics.

Learning Session Objectives

Apply Best Practice Techniques and Cutting Edge Technologies to Organize, Interpret, and Summarize Quantitative Data
Create a Process to Analyze Data and Identify Patterns Not Apparent at First Glance
Reduce “Analysis Paralysis” and Go from Hard Data to Well-Reasoned Conclusions in Less Time
Understand the implications of Artificial Intelligence and Machine Learning in regards to the future of work in the Philippines.

Who Should Attend

This session is suitable to a wide range of professionals but will greatly benefit:

Managers, Supervisors and Team Leads
Business Analysts working as part of an Operations Team
Leaders who oversee business operations

Learning Session Process

Based on a Set of Key Data Science and Analytics Competencies developed by the Asia Pacific Economic Cooperation (APEC), our learning sessions are designed for Team Leaders and Managers to use both in the Philippines and across the region.

Session One – Domain Knowledge & Application: Apply domain-related knowledge and insights to effectively contextualize data, achieved by practical experience and exposure to emerging innovations.

Overview of Big Data, Analytics & Data Science in the Philippines
Cutting Edge Trends in Big Data
How to Apply an Analytics Process to Solving Business Problems

Session Two – Data Management & Governance: Develop and implement data management strategies and governance, incorporating privacy, data security, polices and regulations, and ethical considerations.

The 5 V’s of Big Data
The 3 Tenants of Data Governance
Information Security Guidelines for Filipino Businesses

Session Three – Data Analytics Methods & Algorithms: Capture, clean and inspect data. Evaluate and implement data analytics to derive insights for decision making.

Data Warehouses and Data Lakes
Blending Data from Across the Organization
Cloud Computing and 24/7 Data Access

Session Four – Data Science Engineering Principles for Business Operations: Use analytics software and system engineering principles and modern computer technologies to share findings and tell data stories. Develop analytic processes to improve HR operations.

Analytics with Lean and Six Sigma
Getting IT: the 3’s I and the 3 T’s of Data
Data Science 101: How to Build a Data Science Team

Session Five: Computing Principles for Team Leads: Apply information technology, computational thinking and utilize programming languages to design and develop data analysis processes and techniques.

Optimizing the use of MS Excel for Operations
Mangement Reporting
Working with the IT Team: Buy them Doughnuts

Session Six – Statistical Techniques for Data Analytics: Apply and/or direct the application of statistical concepts and methodologies for data analysis including predictive analytics.

Predictive Analytics Case Study: Google’s Top Performer Model
Tying Management Reporting to Predictive Models
Group Exercise: Build a Top Performer Model

Session Seven – Operational Analytics: Use data analytics and specialized business intelligence techniques for the investigation of all relevant HR data to derive insight in support of decision-making.

Competitor Landscapes and Demographic Profiles
BI Tools Demo: Tableau Public
Social Media Data

Session Eight – Data Visualization & Presentation: Ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies. Build a Business Dashboard prototype.

Data Visualization Guidelines
Group Exercise: Build a Business Dashboard Prototype
The Concept of Enchantment
Data Storytelling Case Study: The Best NBA Team of All Time

Case Studies and Exercises

We will use case studies and group exercises throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

Augment BPO

The Augment BPO Data Science and Analytics Advocacy Project (Augment BPO) is empowering BPO Companies, Executives, and Workers in the Philippines to prepare for and address the clear and present danger posed by Artificial Intelligence Chatbots (AI Chatbots) to BPO revenue growth and jobs through Data Science and Analytics strategy planning, awareness building and upskill training.

DMAIPH

Analytics Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience. If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

Help Me Pick an HR Analytics Topic…

I need your help. I am submitting a proposal to speak at an upcoming HR event being put on by my good friends at Ariva and need help determining which one sounds like the most interesting topic.

Option 1: Insightful HR: Integrating Quality Data towards Better Decisions

Most HR teams are surrounded by an almost limitless wealth of information locked inside business data. However, very few HR teams are consistently able to identify the right data at the right time and even fewer are able to integrate high quality data into the strategic decision-making process. The keys to data-driven decision-making are finding the right balance of analytics Talent, Technique and Technology. I will share a few of tips on how to align the 3 T’s in your business so that HR is able to empower data-driven decision making across the organization. For most HR teams, having good data is the easy part, distilling actionable insights is what makes all the difference

Learning Session Outline:

Learn how to Identify the right data
Discuss how to Inventory the data to gain actionable insights
Discover how to Integrate the data insights into HR decision-making
Unlock the analytics Talent needed for cutting edge HR Analytics
Reveal key analytics Techniques to analyze the data
Master the appropriate analytics Technology to optimize HR decision-making

Option 2: Driving Workforce Performance using Balanced Score Card Metrics and Analytics

Balanced Score Cards have been around since the 1990’s. HR teams across the globe have spent millions in trying to perfect ways to positively drive workforce performance based on metrics. So why is this still a topic of interest? Well, in most cases, it is because score cards and the metrics they report keep pointing us problems that are just not going away. Rising attrition, rampant job-hopping, and lower productivity are challenges we are all dealing with. In many cases, though the problem is not what we are reporting with our scorecards but the data we are populating them. As a whole, we are relying on metrics of the past to describe to us how we got here. What we need though is metrics of the future that accurately predict where we are going. I will share with you several of the metrics of the future I use for workforce reporting in my business and how we employ Predictive HR Analytics to optimize our scorecards.

Learning Session Outline:

Discuss HR Metrics of the Past
Learn about HR Metrics of the Future
Discover how to use HR Predictive Analytics
Design a Data-Driven Scorecard Template

Option 3: Strategic Problem-solving for Better Decision-making: Analytical and Critical Thinking in Motion

One of the biggest strategic challenges facing HR teams is transforming Big Data into actionable insights. The speed in which decision-makers need to act can often preclude the deep understanding of what value actual lies in the data. This causes misguided strategic planning and under informed decision-making across an organization. The best strategic solutions to quicker and more accurate decisions are found in a well rounded HR analytics approach. One that empowers critical thinking not just from the top, but down the ranks. Business Dashboards and Data Storytelling are two tools that should be used to quickly enable quick decisions in real time. I will show you how HR teams are able to keep one eye on strategic problem-solving while still taking care of daily challenges as they pop up.

Learning Session Outline:

Discuss the challenges of HR Big Data
Share HR Strategic Planning best practices
Learn how to get Real Time HR Data
Design HR Tactical Implementations using Analytics
Align HR with Organization-wide Problem-Solving and Decision-Making

Let me know what you think asap!

Thanks!

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Working on an Analytics Internship/OJT program…

400 Hour DMAIPH Data Science & Analytics OJT/Internship Program

The end goal is to develop a DSA strategy presentation for manager. Start out by getting to know the physical data environment, the tools being used and the main players in the business. Move on to assessing the maturity of the analytics culture and it’s use of DSA talent, techniques and technology. Design a business dashboard prototype and deliver a compelling data story to improve management reporting.

Three tracts for interns… HR Analyst, Business Analyst and Data Analyst.

Interns will spend 60% of the internship at the place of business and 40% of the internship in a classroom. This will facilitate the application of theory to real business data in order to help managers get a better idea of the what’s working and what’s nor when it comes to the data in their business.

Based on the APEC DSA Competencies which is close to being adopted by 20+ countries across Asia and the Pacific as a guide for current and future DSA training efforts.

Week 1 – Fundamentals of DSA

APEC DSA Competencies
Company Background
How This Internship Works

Exercise: LinkedIn Profile

Company Deliverable: Company/Organization DSA Profiles

Week 2 – DSA in the Philippines

Putting Data into Context
Emerging Trends
Cultures of Innovation

Exercise: Glossary of Data

Company Deliverable: Defining Where the Cutting Edge Is

Week 3 – Data Management & Governance

Data Management Macro View
Data Governance
Information Security

Exercise: Data Survey

Company Deliverable: Info Security Risk Assessment

Week 4 – Data Analytics Methods & Algorithms

Data Management Micro View
The Right Data
Machine Learning

Exercise: Who’s Who of Data in the Business

Company Deliverable: Data MVPs

Week 5 – Data Science Engineering Principles

Data Map
Identify Right App
Feedback Loop

Exercise: A Visio Data Map

Company Deliverable: Map of Business Data Lake

Week 6 – Computing and Computational Thinking

MS Excel
Query Data
Programming Languages

Exercise: Top 10 Excel Tips Video

Company Deliverable: Top Ten Data Tips

Week 7 – Statistical Techniques

Getting IT
Analytics Maturity Model
Predictive Analytics Model

Exercise: Flight Risk Model

Company Deliverable: Results of Maturity Assessment

Week 8 – Operational Analytics

Management Reporting
Public Big Data
Business Dashboards

Exercise: Tableau Public Mock Up

Company Deliverable: Business Dashboard Prototype

Week 9: Data Visualization & Presentation

Data Visualization
Enchantment
Data Storytelling
Exercise: D.R.A.P.S
Company Deliverable: A Business Data Story

Week 10 – Final Project/DSA Strategy Presentation

My goal is to create and promote a hybrid approach that offers both supplemental education and hands on experience. We need to get past the days of having OJT do data encoding or simple research projects… they need skills that they can apply day one.

They need it, we need it, the country needs it.

Any ideas or suggestions? This is just the first draft.

Hoping to roll this out in the next month or so.

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Asia Pacific Economic Cooperation’s Project DARE initative, DMAIPH champions the use of using data. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in data science and analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

3 Key Tools Needed for HR Analytics: R, SPSS & Tableau

I get asked a lot about what are the best tools to use for HR Analytics. That is not really an easy question to answer as every company has needs a little different then every other company.

That said, the two most common in my experience with HR in the Philippines are R (including RStudio) and SPSS.

R is great for statistical analysis and visualization which is very suited to explore huge data sets.

It enables you to analyze and clean data sets with millions of rows of data. In addition, it lets you to visualize your data and analysis, like what you see below.

RStudio is an open source and enterprise-ready professional software package for R.

It basically does everything that R does, but has a friendlier user interface. The interface contains a code editor, the R console, an easily accessible workspace, and history and room for plots and files. You can take a look at an example of this below.

SPSS is one of the most commonly used HR analytics tools in social sciences. Thanks to its user-friendly interface you’re able to analyze data without having extensive statistical knowledge.

In addition, SPSS is often used within the field of social science. This means that a lot of HR professionals know how to use it, especially the ones with an interest in data.

Additionally, SPSS shares many similarities with Excel which makes it easier to work with.

Tableau is a business intelligence tool that is great at data visualization and business dashboards.

You can also learn to use Tableau to display data you process through SPSS to show results of predictive models.

So for companies looking take the dive into HR Analytics, these tools would give you a good base to inventory and analyze data using R, model it using SPSS and presenting it using Tableau

Analytics in the Philippines – The Philippines is at the center of the action when it comes to solutions to the global need for analytics. Blessed with a solid foundation of young, educated and English speaking workforce, companies around the world are look for Filipino analytics talent to fill analytics positions. DMAIPH was set up to facilitate these solutions and bring the talent and the business together. And that is exactly why I wrote Putting Your Data to Work, the first analytics guidebook designed specifically for the Philippines. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can help you take advantage of this unique global opportunity.

APEC Data Science & Analytics Key Competency #4: Domain Knowledge and Application

According to the APEC (Asia Pacific Economic Cooperation) Advisory Group, Domain Knowledge and Application is one of the key competencies of a Data Science & Analytics professional working in the region.

By definition, a DSA professional can apply domain-related knowledge and insights to effectively contextualize data, achieved by practical experience (e.g. apprenticeships) and exposure to emerging innovations.

In my own experience, I knew Wells Fargo data like the back of my hand, but my domain knowledge would have easily allowed me to the same great things with other big banks. When I toyed with the idea of moving into the health services industry, it was obvious my skills would be useful but I had a lot ot learn about the domain knowledge of healthcare data.

Since, domain knowledge represents knowledge and insight that is unique to the organization or industry and that analysts need to consider when conducting any data project. Without this knowledge, analytics solutions may not entirely address the real business problem.

In my experience, domain knowledge about the data being analyzed can sometimes be acquired through exploration of the raw data. Often, good analysts become subject experts just by playing with the data and asking questions to domain experts about the data.

Given the dearth of analytics talent in many areas, reality will dictate that a lot of data projects will have to be done without sufficient domain knowledge. However, most experts would agree the best results come when the ones using the data, know the data.

So, it behooves companies to invest more in educating and enabling internal resources then looking outside for DSA talent. My solution to this is to introduce apprenticeship programs where subject matter experts train current staff with high DSA affinity who are currently working in other roles.

As an example, there are likely thousands of current call center agents who have the aptitude to be analysts an data scientists, but never had the opportunity to of into DSA. Given they are already employees with proven track records of success, they would be much more likely to have the domain knowledge needed.

If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

APEC Data Science & Analytics Key Competency #3: Data Management and Governance

According to the APEC (Asia Pacific Economic Cooperation) Advisory Group, Data Management and Governance is one of the key competencies of a Data Science & Analytics professional working in the region.

By definition, a DSA professional can develop and implement data management strategies and governance, while incorporating privacy, data security, polices and regulations, and ethical considerations.

The concepts of data management and data governance are kind of the like the chicken… you really can’t have one without the other. Although to the layman, data management includes data governance.

The simplest way to put it, is that data management is the physical aspects of data collecting, capturing, storing, segmenting, etc. Data governance is then the rules or guiding principles that direct how data management works.

There are a lot of data management resources out there. There are not a lot of data governance resources out there. This is why in a majority of companies, we have raw data that needs a lot of cleaning and refining before it can be used in a business.

Organizations that are good in data governance, generally have solid data management. Mature analytics companies have data that is easy to access, is accurate and is used in decision-making.

Data Governance is composed on three parts: People, Process and Technology.

DMAI_DataGovernance The people have titles like database admins, data stewards and data warehouse experts. They enforce the laws and rules around data within an organization.

The technology used is generally programming languages, coding and joining data structures to layout the blueprint of how data flows throughout the organization’s hardware.

The process is the rules, generally set down by senior management, and often in line with government or industry regulations that govern how data should be used.

If your organization has a lot of data, has people that are well versed in data management, and uses data to feed decision-making, then you need to make sure you have solid data governance.

If you don’t, DMAIPH can help. Likely you are missing key people, clear processes, and/or the right technology to ensure your data is being governed correctly.

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Worried Your Call Center Job Might Be Taken by a Robot? You should be.

http://news.abs-cbn.com/business/05/12/17/bpos-gearing-up-for-impact-of-artificial-intelligence-on-industry

I shared this article on an FB group and got a lot of inquires from people who are indeed seeing an opportunity to move from a call center job to a Data Science and Analytics (DSA) job.

Most of the questions revolved around how to transition.

Want to get Data Science and Analytics Training. Not sure how, here are some tips!

Self-Teach a Skill. (YouTube has thousands of free resources)
Volunteer at Work. (Find out what skills are in demand in your company and ask if you can help)
Take a Training Class (there are a lot of public training classes out there, including some that DMAIPH does).
Read a Book (Experts share a lot… like my book Putting Your Data to Work: An Analytics Guidebook for Filipino Professionals)
Find a Mentor (Jedi Knights start as an apprentice, so do many analysts and data scientists)
Join a Group (there are a lot of meet up groups like Data Science Philippines you can use to network)
Go Back to School (a few dozen schools here in the Philippines are either already offering data science an analytics programs are kicking them off soon)
Follow a Blog. (Besides reading books, there are a lot of good ideas shared on blogs like mine, dmaiph.com)
Become a Member (join associations like aap.ph aka Analytics Association of the Philippines)

Another question that came up often was, “What should you learn first?”

Find a tool, technique or technology that is high demand and fits your interests and aptitude. The best way to find out what to focus on is do a job search for the kind of job you want and look at the requirements. For newbies some of the in demand skills are

SQL (the most widely used language used for data analytics)
Microsoft Excel (if you know pivot tables, simple formulas and can make decent visuals you will be in high demand)
Tableau (a free version called Tableau Public can be downloaded and is easy to learn)
R (the most widely used tool for predictive analytics and data science and its free)

And then a lot more people added me on FB, hoping to network and find new opportunities. Thats a good tip too. Networking is key.

DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience.

jobspicture2 If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

Also if you own or manage a call center, we can help. In fact, DMAIPH has successfully set up Filipino analytics teams for over a dozen U.S. based businesses. Offering both virtual and office based teams that specialize in problem solving using data, new technology and analytics techniques is our strength.

Finding and empowering analytics talent is increasingly challenging, but we have mastered Surfing Into The Storm and can show you how to succesfully set up a team. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn more about how to set up an analytics-centric team in the Philippines.

Teaching Analytics: APEC List of Competencies

Teaching Analytics: An Instructor’s Guide to implementing the recommendations of Project DARE (Data Analytics Raising Employment).

APEC (Asia Pacific Economic Cooperation) hosted an event on May 4-5 bringing together over 50 analytics experts and visionaries from over 14 counties across the Asia-Pacific region to form an advisory group.

The APEC Project DARE (Data Analytics Raising Awareness) Advisory Group started with an agenda set to develop recommended “APEC Data Analytics Competencies.

There are still being finalized, but as of last week here is a high level of the competencies that we came up with:

Business and Organizational Skills

Operational Analytics: Use data analytics and specialized business analytics (i.e. business intelligence) techniques for the investigation of all relevant data to derive insight in support of decision-making.
Data Visualization and Presentation: Ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies.
Data Management and Governance: Develop and implement data management strategies and governance, incorporating privacy, data security, polices and regulations, and ethical considerations.
Domain Knowledge and Application: Apply domain-related knowledge and insights to effectively contextualize data, achieved by practical experience (e.g. apprenticeships) and exposure to emerging innovations.

Technical Skills

Statistical Techniques: Apply statistical concepts and methodologies for data analysis.
Computing: Apply information technology, computational thinking and utilize programming languages and software and hardware solutions design and development for data analysis.
Data Analytics Methods and Algorithms: Capture, clean and inspect data. Evaluate and implement data analytics and machine learning methods and algorithms on the data to derive insights for decision making.
Research Methods: Utilize the scientific and engineering methods to discover and create new knowledge and insights.
Data Science Engineering Principles: Use software and system engineering principles and modern computer technologies, incorporating a data feedback loop, to research, design, and prototype data analytics applications. Develop structures, instruments, machines, experiments, processes, and systems to support the data lifecycle.

Workplace Skills

21^st Century Skills: Exhibit crosscutting skills essential for DSA at all levels including, but not limited too; collaboration, customer focus, communication and storytelling, organizational awareness, critical thinking, planning and organizing, problem solving, decision making, business fundamentals, awareness of social and societal awareness, intelligibility, cross cultural awareness, dynamic (self) re-skilling, professional networking, ethical mindset and entrepreneurship.

Once this list is finalized I will update you all.

My end goal is two fold, (1) to help craft a version of the competencies into an academic discipline that the Analytics Council can present to CHED for adoption and (2) to design a vocational education track to address the basic skills needed for entry level DSA work here in the Philippines.

Stay Tuned!

Become a Data Science & Analytics Pro! Apply for the DMAIPH Apprenticeship Program

A standard definition of Apprenticeship is a kind of job training that involves following and studying a master of the trade on the job instead of in school.

Learning to become an analyst for the most part has been something done on the job. after working in a company and gaining subject matter expertise, those who had good analytics skills often found themselves going down the analyst career path.

Big Data and technological advancements in analytics processing and data science have changed all that.

Nowadays, there are so many analyst jobs available that the natural order of learning to become an analyst isn’t working fast enough.

Higher education is trying to come up with solutions to offer analytics themed course, a few are already in place. But that’s only training 100’s when industry needs 1,000’s.

SO, to help fill the skills gap between the very finite supply of Data Science and Analytics (DSA) talent and the huge demand in the form of open jobs, we have to get outside the box.

You will see a lot more ideas like the DMAIPH Data Science & Analytics Apprenticeship program coming in the near term.

But don’t wait for the future, get ahead of the game.

Learn the DSA skills you need for a long and profitable career as an analyst.

E-mail me your resume today if you would like to learn more. danmeyer@dmaiph.com

I will be taking on a few more apprentices in the coming months as we grow the program to implement APEC’s Project DARE recommended approach to gaining a basic understanding of what it means to be a DSA professional.

Hope to hear from you soon!

Dan

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Why Focus on Data Analytics Competencies?

Later this week I will be attending the APEC Project DARE (Data Analytics Raising Awareness) Advisory Council in Singapore to discuss Recommended APEC Data Analytics Competencies.

Why Focus on Data Analytics Competencies?

Jobs requiring a familiarity with data analysis are forecasted to dramatically rise, resulting in a massive shortage of qualified employees. According to reports, some economies face a shortage of up to 1.5 million data analytics-enabled managers and analysts, costing billions of dollars in lost revenue annually. There is an urgent need to ensure that the future workforce is equipped with data analytics competencies to secure the jobs of tomorrow and move with ease in the labor market.

This is where Project DARE comes in. Project DARE aims to facilitate development of a data analytics-enabled workforce across the APEC region to effectively support sustainable economic growth and prosperity in the Asia-Pacific region. To do so, Project DARE developed a set of Recommended APEC Data Analytics Competencies which will be a resource to academic institutions and governments to align curricula, courses and programs so APEC economies are equipped to educate its workforce with the data analytics skills needed by employers in a data-driven future.

How was the Recommended Data Analytics Competencies Developed?

The Recommended APEC Data Analytics Competencies was developed through a public-private partnership with input from over 40 Advisory Group members (see Acknowledgements) comprised of distinguished business and higher education leaders who oversee data science and analytics needs for their organization and data science inter-disciplinary initiatives and curriculum. The Advisory Group was led by the private sector partner co- chairs, global skills and knowledge company Wiley and the Business Higher Education Forum (BHEF), with technical support by the EDISON (Education for Data Intensive Science to Open New Science Frontiers) Project.

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DMAIPH and Analytics Education

Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Data Science Philippines Meetup Group, DMAIPH champions the use of using data. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

About Project DARE

Project DARE is an initiative of the Asia-Pacific Economic Cooperation led by the United States (U.S. Department of Labor) with co-sponsorship from the governments of Australia, Japan, Malaysia, Peru, Chinese Taipei, and Viet Nam. As a project of APEC’s Human Resources and Development Working Group (HRDWG), Project DARE seeks to enable APEC workforce with the data analytics competencies demanded by employers today and to secure the jobs of tomorrow.

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