The Analytics Puzzle for Higher Education in the Philippines

When you look at the picture on the box of puzzle pieces, you generally think it won’t be so hard to fit all the pieces together. But then when you lay out all the pieces and connect them one by one it can often feel like a sense of this is a lot harder then I thought.

In many way, that’s how I feel about efforts to date regarding the teaching of Data Science and Analytics in the Philippines. The end product is clear, just about all the 2,000+ HIEs across the Philippines offering some level of DSA education to a wide range of students.

Everyone agrees that we need more education to meet both the high current demand and the expected huge future demand for DSA talent for both domestic and global consumption. We have seen a lot of awesome initiatives popping up trying to train educators to teach DSA subjects and have seen a number of industry-academe partnerships. CHED has even set aside significant resources to promote the training of faculty and the incentive to offer DSA programs.

So things are going well, but when you look at the simple math of how many educators need to be training in the very near future, some like me get a little concerned. Current programs train a few dozen here and maybe a few hundred there, bit by bit. But if you need thousands then current efforts are just going to come up short.

What we need is a unified front. Bringing together all the interested parties, many of whom are already working on this issue, is the only way to get to critical mass. By my estimation we should be looking at training 5,000 educators in the next 3 years. And a one week overview is just the start. To really become adept at teaching DSA, educators need an apprenticeship that lasts months to really learn the tools of the trade like data storytelling, business intelligence and predictive analytics.

And that is just the faculty… when you think about the 100,000s of students who need to taught DSA, you start to see that this puzzle is gonna take a lot more effort to complete then it may have looked like at first.

So thats where I am at now… both evangelizing and empowering. Raising awareness of what the puzzle looks like when solved and why we need to solve. And empowering to build collaborations to connect the pieces faster then each puzzle expert can work on their own.

And that is exactly why I started Augment BPO.

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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.

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DMAIPH 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.

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Top 5 Reasons to Attend the Digital Transformation Summit 2017

From the Global Chamber® Manila Newsletter

May 9, 2017

  1. Be inspired by an all-star lineup of speakers, who are already gaining significant benefits from adapting new technologies
  2. Learn about various technological platforms such as AI, IOT, Big Data, Analytics, and how it’s disrupting businesses
  3. Reflect, reexamine your company’s issues and goals, and set your vision and new strategy for the next decade
  4. Engage and network with executives and fellow thought leaders
  5. Empower the culture of innovation within you!

Not registered yet? It’s not too late to sign up!

I will be one of the speakers, talking about Data Storytelling. It is quite an honor to part of this awesome event! 🙂

Attend one or both days of the Digital Transformation Summit this May 24 and 25 at SMX Aura Convention Center.

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.

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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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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.

The Rock Stars of Data: Big Data Analytics & Data Management

How to master big data analytics and data management?

The Rock Stars of Data: Big Data Analytics & Data Management

2-day Class: Big Data Analytics and Data Management

June 27-28, 2017

Discovery Suites, ADB Ave., Ortigas Center, Pasig City

9AM-5PM

Rock Stars of Data Series: Big Data Analytics & Data Management

Data Rock Stars Dan Meyer (DMAIPH) and Dominic Ligot (Cirrolytix) have joined forces to offer a unique training focusing on both the Analysis and the Management of Big Data.

To find out more about our next scheduled public learning session on May 18-19, 2017 in Ortigas or to set-up an in-house training, send an e-mail to analytics@dmaiph.com

Learning Session Description

Building The Data Value Chain. Data is pervasive – everything we do in the modern world uses and generates data in some shape or form: from web sites we surf, the social media we consume, to the mobile devices we use to connect and communicate. Modern businesses also use and generate data, from financial data, to customer data, to transaction data and sensor data.

But data is only a raw material. Regardless of amount, the real importance of data is only determined by the value people and businesses derive from it. Getting data is the first step. Then the challenge becomes transforming the raw material into a processed good: information. Information enables decisions, and decisions create value.

This session is about the basics of transforming data into information: the data value chain. Attendees will learn how to identify the right data, about how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

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This seminar will lightly touch on each aspect of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, Tableau and SQL, but is designed for those with little to no prior experience with these tools.

Learning Session Objectives

  1. Apply cutting edge technologies to organize, interpret, and summarize Big Data in your business.
  2. Create a process to analyze data and identify patterns not apparent at first glance
  3. Understand the components of The Data Value Chain: Ingestion, Storage, Transformation, Analysis – and how they are all important to deriving value from data.
  4. Learn database manipulation and processing basics using the Structured Query Language (SQL)
  5. Connect a data analysis tool such as MS Excel or Tableau to a database to be able to perform analysis on processed and stored data

In this session, your organization will be able to use:

  • Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
  • Critical marketing steps of orientation necessary before engaging tools and technology
  • How to simply and quickly amplify decision making by separating the signal from the noise
  • A framework for asking the right questions, allowing the ability to link analytics to business strategy

In this session, your participants will be able to:

  • Learn the best practices for organizing, summarizing, and interpreting quantitative data
  • Create a repeatable process for analyzing your data
  • Shorten the time between analysis and action to avoid “analysis paralysis”
  • Know how to get from hard data to well-reasoned conclusions

Who Should Attend

  • Business Analysts, Data Analysts and other Analytics Professionals
  • Business professionals who are involved in day-to-day analysis of data.
  • Data analysts who are already performing analysis using spreadsheets but struggle with manual data processing.
  • Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.
  • IT and Development Staff that work closely with business leaders and decision-makers.

Section One – Big Data—It’s Not Just Size That Matters

  • Understand the 3 T’s of Analytics: Talent, Technique and Technology.
  • Describe the importance of effectively, analyzing big data in Business today.
  • Develop a Data Map to analyze the Big Data in your Business.
  • Recognize when to employ Descriptive, Predictive or Prescriptive Analytics.
  • Establish clear objectives when analyzing Big Data.

Section Two – Assess Your Current Analytics Culture

  • Define What Is an Analytics Centric Culture.
  • Describe the issues and trends in today’s analytics field.
  • Discover how to find the most important KPIs.
  • Learn how to build better management reports.
  • Optimize your use of MS Excel for Big Data Analytics

Section Three – Using Business Intelligence Tools

  • An overview of BI Tools.
  • Tableau Public Demonstration,
  • Discuss the Concept of Data Visualization.
  • Build A Business Dashboard Prototype.
  • Apply a Process to Present Big Data Clearly.

Section Four – Interpreting Your Data and Analysis

  • Articulate the importance of accurately interpreting Data.
  • Determine how to validate your data analysis.
  • Mitigate and analyze Risk, Uncertainty, And Probability.
  • Spot patterns and trends through Statistical Analysis.
  • Use findings from Big Data to Drive Decisions within your Organization.

Section Five: Presenting the Data Value Chain and Databases

  • Discuss the components of The Data Value Chain and the various users and roles involved in transforming data to value: Database and ETL engineers, Data analysts, Business users.
  • Learn about basic data architecture and the role of databases in processing data.
  • Understand the basics of databases, tables and views.
  • Learn about the Structured Query Language (SQL) and SELECT statements.

Section Six: Data Processing with SQL

  • Discuss the additional value that can be derived from using SQL for Data Processing.
  • Go into detail on various ways of processing and preparing data using SQL.
  • Learn about aggregates, conditions, how to join tables, and run queries within queries.

Section Seven: Accessing SQL Tables with Excel

  • Learn about Open Database Connectivity (ODBC) and how Excel uses ODBC to connect to external data sources.
  • Discover how SQL tables and views can be read by Excel into instant Pivot Tables and Pivot Graphs.
  • Understand how changes in database table or view via SQL Inserts, Deletes, and Updates are reflected on Excel.

Section Eight: Performing analysis of SQL-based data using Excel

  • Learn about how SQL data can be dissected using the Data Analysis functions in Excel.
  • Talk about form tools and macros that can automate manual reporting.
  • Discuss tips for reporting and sharing the results of your analysis.

Minimum Hardware and Software Requirements.

  1. Laptop with Intel Core i3 and 4GB RAM.
  2. Windows OS with Excel 2007 or greater.
  3. ODBC and database connections will be provided during class.

Case Studies and Exercises

Dan and Doc 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.

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Learning Investment for 2-day Seminar:

Exclusive Offer!!

Early Bird Rate

P 12,000.00 + VAT

(Pay the full amount on or before April 20, 2017)

Group Rate (Minimum of 5)

P13,000.00 + VAT

Regular Rate:

P 14,600.00 + Vat

(starting April 21, 2017)

All investments includes: 2-day Analytics Seminar with two of the most in-demand Analytics and Data Management Guru in the Philippines, complete with Training Materials, AM/PM Snacks, Lunch and Certificates.

ABOUT THE SPEAKERS

Dominic Ligot, Data Scientist

Doc’s areas of expertise focus on Fintech, Big Data Analytics, and Digital Transformation.

Click here to see Doc’s full speaker/trainer profile >>>

Daniel Meyer, Analytics Champion

Dan specializes in a variety of analytics themed training and speaking option including HR& Recruitment Analytics, Data Analytics, Data-Driven Decision-Making and Analytics for CEO’s.

Click here to see Dan’s full speaker/trainer profile >>>

Reserve your seat here >>>

 

Data Science Philippines – Feb 2017 Meet Up

My talk is the 2nd one, a little over half way through the video. Listen first to some real data scientists talking about their trade, then it’s my turn where I talk about just how many data scientists there are in the  Philippines right now. Thanks to DataSeer for asking us to sponsor and for setting up the event. Looking forward to many more to come! 🙂

Q7: What exactly is data science and why the rapid rise of data scientists?

A year ago I might have found it challenging to really answer this question. The first time I had heard of the term data science and a data scientist wasn’t that long ago. And I have been doing some pretty advanced analytics for close to 20 years now.  I know the term has been around in academic and research circles awhile longer, but 2014 is the first time I ever saw a job posting for data scientist in big business.

So what is data science? Besides simply being the study of data, it generally refers to using complex models, machine learning, predictive and prescriptive analytics and powerful technology to analyze business data in much greater volume, velocity and variety then possible a few years ago.

And of course the ones charged with doing the data science are data scientists. They understand math, statistics, and theories that can be applied to business data using new technologies and methodologies.

The biggest challenge to being a true data scientist is that you have to be adapt at both technology and working with people. Being a business data expert, knowing how to code and doing higher math are only half the job. You have to also share your data, communicate it in ways that drive action, share and engage with non-data centric people. It’s hard to find people who are good at both.

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Image from Forbes Magazine. 

In addition, whole some data scientists are educated to be data scientists, very, very few actually have any kind of degree in data science. That kind of degree really didn’t exist until very recently. Instead most data scientists have advanced degrees is related subjects and have migrated into the business world do to market demand.

That demand has been growing at a staggering rate the past few years as every day we generate more and more data across the planet. President Obama first employed a data scientist for his campaign in 2012. The White House now has a chief data scientist position.

If you were to compare results from job board searches form 2012, you’d see maybe 100 data scientist job postings. Now its easily in the 1000’s.  So that’s why the job market for data scientist is one of the hottest around.  Lack of training programs, having both tech and people skills, and the booming demand due to unending new data to being analyzed.

Some people ask me if I’m a data scientist I am careful with my answer. True data science is not something I am academically prepared for nor I have never published anything in a scholarly journal. But my real world experience working with data has made me an expert on many aspects of data science.

I guess I feel more like an analyst, but a freakin awesome analyst who can do a lot of things using data that are super important to a business.

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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.