Top Data Science & Analytics Skills in Demand: 2017 vs 2022

One question I get asked a lot are what are the best skills to master for Data Science & Analytics (DSA) jobs right now?

Another question is what skills will be in demand five years from now.

With both questions, most of the ones asking are looking for specific applications or tools to learn. Often my reply is that it really doesn’t matter which tool or application you use as much as you get practical experience working with data.

My point is that job titles and technical skill sets come and go as technology evolves… what you really need to do is be in a place where your curiosity and critical thinking are continuously challenged. It helps to also be somewhere that encourages new solutions and has a culture that fosters innovation.

Not easy to find, but thats more important to me then what you learn now. That said, I still have to answer the questions with some sense of what to learn and master so…

Here are some of the top DSA skills needed right now:

  • Management Reporting
  • Advanced Excel
  • Familiarity with Business Intelligence Tools
  • SQL Coding for Teradata Databases
  • Transforming Data Warehouses into Data Lakes
  • Business Dashboards and Data Visualization with Tableau
  • Predictive Analytics with R and Azure
  • Predictive Model Building with SPSS
  • Data Storytelling

By no means a exclusive list… if you do a quick search of job posting for DSA professionals you will not find two job posts with the exact same requirements.  From where I sit, these are just the ones I see a lot.

When it comes to the future, I did a quick search and came up with this list…

Here are some of the top DSA skills likely needed over the next 5 years.

  • Natural Language Generation and Text Analytics
  • Human/BioMetric Analytics
  • Machine Learning
  • Prescriptive Analytics
  • Chat Bot Design and Maintenance
  • AI Virtual Assistants Design and Programming
  • IoT Sensor Analytics

Again… not even close to a complete list, but you can get a sense of where things are going.

Assuming most companies mature past the basic analytics phase and that we continue moving towards AI solutions at the current pace, there will be a lot of new analyst jobs out there with new titles. Data Scientists will be busy solving a wide range of data challenges that currently still seem like Science Fiction today.

At least that’s my take as of now.

It will change.

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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.

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

  1. Apply Best Practice Techniques and Cutting Edge Technologies to Organize, Interpret, and Summarize Quantitative Data
  2. Create a Process to Analyze Data and Identify Patterns Not Apparent at First Glance
  3. Reduce “Analysis Paralysis” and Go from Hard Data to Well-Reasoned Conclusions in Less Time
  4. 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.

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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 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.

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.

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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.

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_DataGovernanceThe 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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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.

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!

  1. Self-Teach a Skill. (YouTube has thousands of free resources)
  2. Volunteer at Work. (Find out what skills are in demand in your company and ask if you can help)
  3. Take a Training Class (there are a lot of public training classes out there, including some that DMAIPH does).
  4. Read a Book (Experts share a lot… like my book Putting Your Data to Work: An Analytics Guidebook for Filipino Professionals)
  5. Find a Mentor (Jedi Knights start as an apprentice, so do many analysts and data scientists)
  6. Join a Group (there are a lot of meet up groups like Data Science Philippines you can use to network)
  7. 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)
  8. Follow a Blog. (Besides reading books, there are a lot of good ideas shared on blogs like mine, dmaiph.com)
  9. 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.

jobspicture2If 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.

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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

  1. 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.
  2. Data Visualization and Presentation: Ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies.
  3. Data Management and Governance: Develop and implement data management strategies and governance, incorporating privacy, data security, polices and regulations, and ethical considerations.
  4. 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

  1. Statistical Techniques: Apply statistical concepts and methodologies for data analysis.
  2. Computing: Apply information technology, computational thinking and utilize programming languages and software and hardware solutions design and development for data analysis.
  3. 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.
  4. Research Methods: Utilize the scientific and engineering methods to discover and create new knowledge and insights.
  5. 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

  1. 21st 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!

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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.