How Many Data Scientists are There and is There a Shortage?

Recently saw this article on KDnuggets (check them out if you aren’t already subscribed) and thought it was worth using to update some of my slides about the current talent shortage for Data Science & Analytics (DSA) skills.

This shortage is definitely acute here in the Philippines.

The 2011 McKinsey report on Big Data said that “The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of Big Data.”

In 2014, KDnuggets examined “How Many Data Scientists are out there?” and came with an estimate of 50-100,000, and did not see much evidence of a massive shortage then. In 2014, we found only about 1,000 job ads for “Data Scientist” on indeed.com.

Now that we reached 2018, KDnuggets has examined how accurate were those predictions and tried to answer three questions:

1. Is there a shortage of Data Scientists now?

2. How many “Data Scientists” are there , both in name and in function ?

3. What are the future prospects for Data Scientists?

The answer to the first question is a resounding YES!

LinkedIn Workforce Report for US (August 2018) says “Demand for data scientists is off the charts … data science skills shortages are present in almost every large U.S. city. Nationally, we have a shortage of 151,717 people with data science skills.
Note that LinkedIn reports shortages for people with “Data Science Skills”, not necessarily people with “Data Scientist” title.
We can estimate the demand for “Data Scientists” from two popular job search sites – indeed and Glassdoor.
Search on indeed.com for “data scientist” (in quotes) in USA finds only about 4,800 jobs. However, in a search for data scientist without quotes, about 30,000 jobs.

US is the largest but not the only market for Data Scientists. We can also see strong demand for Data Scientists elsewhere:

UK: 1,100 jobs
Germany: 900 jobs
France: 718 jobs
Philippines: 599 jobs — You Read That Right! More than India.
India: 500 jobs

Glassdoor search for “Data Scientist” finds about 26,000 jobs in USA (same results if quotes are removed).

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Question 2: How Many “Data Scientists” are There, Both in Name and in Function?

Google search defines a data scientist as “a person employed to analyze and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.”

There are many people in the industry and academia who do this work without having the formal title of a data scientist, since Data Science is an interdisciplinary field at the intersection of Statistics, Computer Science, Machine Learning, and Business. We can estimate the current population of Data Scientist by examining popular data science platforms.

Kaggle (now part of Google) is a platform for data science and analytics competitions. It claims to be the world’s largest community of active data scientists.

While not all Data Scientists take part in Kaggle competitions or have a Kaggle account, and not all Kagglersdo work of data science, it is reasonable to assume a large overlap.

On Sep 19, 2018 Kaggle says they surpassed 2 million members in August 2018.

Since not all Kaggle members are active, Kaggle membership is probably a global upper bound for people engaged in data science.

KDnuggets is now reaching over 500,000 unique visitors per month.

KDnuggets now has about 240,000 subscribers/followers over Twitter, LinkedIn, Facebook, RSS, and email.

On LinkedIn, there are many groups dedicated to data science, and although the engagement in those groups has been falling, we can use their membership as a rough estimate. Here are three of the largest groups

Big Data and Analytics – 339,000
Data Science Central – 278,000
Data Mining, Statistics, Big Data, Data Visualization, and Data Science – 170,000

Searching LinkedIn for “data scientist” (quotes are important) we find over 100,000 people with that actual title. So if globally between 200,000 and 1,000,000 people are doing some Data Science related work, then a majority of them does not have a Data Scientist title.

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We can also estimate the by looking at activities related to languages and platforms most connected to Data Science: R, Python, Machine Learning libraries, Spark, and Jupyter.

Apache Spark Meetups had 225K members recently and growing every month.
Intel Capital estimated that there 1 million R programmers worldwide.
Based on the public data on python.orgwebsite, there have been around 2.75 million downloads.
Jupyterproject has around 3 million users at present.

These numbers can give us a rough upper limit on the number of data analysts/data scientists around the world.

So yeah, to answer the question, there are at least 200,000

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Question 3: What are the Future Prospects for Data Scientists?

The near-term future for Data Scientists looks bright.

LinkedIn 2017 emerging jobs report claims that machine learning engineers working today has increased by 9.8 times as compared to 5 years ago.

Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. Data scientist roles have grown over 650% since 2012.

Job growth in the next decade is expected to outstrip growth during the previous decade, creating 11.5M jobs in the Data Science/Analytics area by 2026, according to the U.S. Bureau of Labor Statistics.

IBM recently claimed that by 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2,720,000. No matter what the true number of data professionals out there currently, their number is likely to grow in the near future.

So What are the Future Prospects for Data Scientists in the Philippines?

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Based on Data from APEC (Asia Pacific Economic Cooperation), there is both a huge demand here in the Philippines as well as in the jobs where the Philippines already has an outsourcing pipeline too.

SO what does that mean for you?

You Need to Know Exactly What You Need to Hire/Learn how to have/be a Data Scientist?

And it’s not easy.

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To assemble a team of DSA Practitioners, you need to make sure you have the right combination of talent.

Here is how I would start.

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Make sure you have people who can do these functions.

And if you want to learn how to be one of these key players, I’m betting you need to know where to start.

So wether you want to be a DSA enabled professional or you want to assemble a DSA team, here is a better understanding of how that looks.

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Yeah I know. It is a lot!

So, what now?

Connect with DMAIPH and we will get you started!

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DMAIPH – Decision-making, Analytics & Intelligence Philppines

Over the past few years businesses in the Philippines have invested heavily in big data, analytics and data science, but still have not achieved the expected outcomes of data-driven companies.

Based on our learnings from the 100’s of Filipino businesses and 10,000s of Filipinos who have taken part in DMAIPH Analytics trainings all across the country, we have crafted a proven, non-technical approach to upskilling your team in analytics.

In 2019, we will be launching two new training programs: (1) Our DMAIPH Applied Analytics Master Class series for executives, leaders and decision-makers and our (2) DMAIPH Applied Analytics Boot Camp series for practicing analysts.

We will feature case studies of real Filipino run business, exercises based on actual analytics challenges being solved by Filipino analysts, and provide you with a copy of my book, Putting Your Data to Work, an analytics guidebook for the Filipino professional

Connect with us via our marketing partner, http://www.sonicanalytics.com to learn about upcoming analytics trainings and events.

The AAP Analytics Internship Matching Program

Innovating the Data Science & Analytics Internship Experience in the Philippines.

The Analytics Association of the Philippines will offer a Data Science and Analytics Internship matching program for Filipino students and employers. The AAP will serve as a conduit and catalyst bridging theory and application to ensure value to the company as well.

Our program has been developed to address 3 current challenges facing students and employers when it comes to data science and analytics themed internships:

students are often given menial tasks that do not apply knowledge / learned theory
mechanisms do not address disconnect between areas of interest and areas of need
companies are not able to effectively identify parts of the value chain that can be assigned to interns while causing no substantial risk to the business’ operations

By enrolling in the AAP DSA Internship Matching Program, students will be matched with employers that provide opportunities to learn and practice DSA skills that are in high demand in the workforce. Students can also be fast tracked for employment post-graduation by their match in a more continuous process.

By enrolling in the AAP DSA Internship Matching Program, employers will be matched with students that are committed to learning DSA skills that can add value to the employer’s business as well as provide a more seamless path to career placement.

Employers will also be encouraged to take a more active role in providing, business cases, data sets and resource speakers for the programs the students they are matched with come from. By being more involved with their students before and after the internship, the bridge between academia and industry will be optimized.

To this end we have developed the following process that will kick off on January 15,2018:

Students apply for OJT matching with AAP
Employers apply for OJT matching with AAP
AAP Matches students and employers based on profiles
AAP conducts orientation for students and employers
AAP provides online resources to both students and employers

The AAP will assess partner schools and their respective tracks and courses that could work on analytics (end-to-end of value chain) The AAP will also define areas of expertise of each program based on the APEC DSA Competencies and the AAP DSA Framework. Students will be interviewed and vetted.

Additionally, the AAP will provide a matrix of industry partners and corresponding needs (with parts of the value chain, doesn’t have to be siloed, can cover multiple parts)

As for the employer, they will:

Define problems/needs (could be something students can work on parallel to an existing team effort)
Define final output (paper/study, running program, a presentation, proposal, working product, solution)

As for the schools, they will:

Provide 1-2 professors to assist in mentorship
Conduct processing of internship experience to give feedback to AAP

Overall our goal is to offer a unique value proposition by facilitating internships with a view of work as an end-to-end process that involves deep-diving into a specific problem or project of the company. The companies enrolled in our program get real value out of internships besides serving as a marketing tool.

With our network of industry partners, prestigious academic institutions and analytics thoughts leaders, the AAP is well positioned to facilitate significant change in the way analysts and data scientists are born.

Our Analytics Internship Matching Program will go a long way in providing tomorrow’s workforce with in demand skills that employers covet, which in turn will allow the Philippines to be a world leader in analytics talent.

Most of the credit for the content of this post goes to Mel Awit, the AAP Analytics Manager.

DMAIPH is a founding member of the Analytics Association of the Philippines (AAP.PH) and specializes in arming the Data-Driven Leader with the tools and techniques they need to build and empower an analytics centric organization. Analytics leadership requires a mastery of not just analytics skill, but also of nurturing an analytics culture. We have guided thousands of Filipino professionals to become better analytics leaders. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to discuss a uniquely tailored strategy to ensure you are the top of your game when it comes to Analytics Leadership.

I Need Analytics Training. Where Do I Start?

If you put yourself in the mind of the typical Filipino professional looking for analytics training, it is not easy to figure out where to start.

The ecosystem is not very unified, with a hodge podge of public training solutions available and only dozen or so schools offering analytics.

To someone who is relatively new to using big data to solve business problems, it can all seem very nosebleed inducing as well. Data science, predictive analytics and machine learning can all sound complicated and expensive.

So where do I start? That is a very common question I get asked when I talk about analytics in the Philippines.

The answer comes in three parts. First we need a framework to set certain standards and definitions of what a Data Science and Analytics enabled professional should know.

We base that on the set of 10 DSA competencies as defined by APEC’s Project DARE,

(Props to my fellow AAP board member Sherwin Pelayo for the awesome images)

Since few people need to know everything about everything, it is best to figure out which competencies you want to focus on first.

Once you have an idea of where to start, then the next step is determine what kinds of job skills match the competencies you are looking to develop.

This can be done by determining where in the data life cycle you are looking have an impact,

Once you have a firm idea of the skills you want to build and where they fit into the analytics life cycle of your business, then it is a matter of planning out how to level up.

This is where the AAP has take APEC’s competency list and broken then out across the various job functions along the analytics life cycle by level of skills required.

This allows us the ability to determine where we are in terms of analytics maturity and design the appropriate plan to level up.

And that will lead you to one of the AAP member companies for the appropriate type of corporate training or to one of the AAP member schools for the right higher education solutions.

And that is how you can get a better idea of what type of analytics training is best for you and your business to get started with.

Analytics Leadership – DMAIPH is a founding member of the Analytics Association of the Philippines (AAP.PH) and specializes in arming the Data-Driven Leader with the tools and techniques they need to build and empower an analytics centric organization. Analytics leadership requires a mastery of not just analytics skill, but also of nurturing an analytics culture. We have guided thousands of Filipino professionals to become better analytics leaders.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to discuss a uniquely tailored strategy to ensure you are the top of your game when it comes to Analytics Leadership.

Analytics Education = Out with the Old, In with the New

Having spent the last 5 years talking about analytics here in the Philippines, it seems we are finally at a place where a significant percentage of leaders and decision-makers are now aware that they need a good analytics strategy for their business to succeed.

Now that we are finally at point where people in power get, we have another challenge. Just because they get it doesn’t mean they know how to enable it.

In fact most of our current solutions to educate and train when it comes to analytics seems to be a bit old fashioned. Analytics evolves much faster then traditional education models can keep up with.

In fact, most people learn analytics on the job. Some attend public trainings. A few receive practical experience while in school. Very few learn in vocational or apprentice like programs.

Almost all the training is done in person, with an expert teaching in a classroom setting.

Most of the training is done by talking theory and doing some exercises on mock data.

Due to data privacy issues, few companies allow employees to get up skill training while using their own data and towards solving real business problems.

To compound the challenge, there are a precious few analytics experts to go around to meet the surging demand for analytics education and training.

When I do the math… 500,000 Filipinos need analytics training in the next 5 years to ensure we can deal with the wave of digital transformation the world in undergoing.

So now what?

It’s easy to say online training is the solution. And it is part. But just filming a training and reshowing it loses a lot of the impact. When learners aren’t engaged they struggle to absorb most of the content.

So live online classes that have an interactive ability are key.

Harnessing the power of YouTube and looking at things like TED talks give us some ideas.

Formal corporate trainings can be supplemented and eventually superseded by meet-up groups and more informal learning sessions.

Formal education has to transition more from the class room and to on the job.

Right now, students spend 90% of their time in classroom and less then 10% on the job working with real data solving real problems. Many schools struggle with educating on analytics topics because they don’t have qualified professors.

Lets flip that around. Let the subject matter experts working in the field do more of the education in the workplace.

That’s just three ideas; Interactive Analytics Talks, Optimizing Meet Up Groups and much more dynamic On the Job training.

What else can we do to shot for the moon?

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.

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.

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.

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 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.

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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APEC Data Science & Analytics Key Competency #2: Data Visualization and Presentation

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

By definition, a DSA professional demonstrates the ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies.

Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Being able to present these visuals in a way that initiatives action and empowers decision-making is just as important.

The best data visualizations are simply ones that take data and convert it to visuals like pie charts, line graphs, sales charts, etc.

Patterns, trends and correlations that might go undetected in spreadsheets or text-based data can be exposed and recognized easier with data visualization software.

Good analysts are the ones who can visualize data and use tools to add a story telling component to their analysis.

One of the best ways of communicating any kind of complex information is to turn it into a story, starting at the beginning and working your way through to the end.

Making the story relevant to the audience is key. By making the results both easier to understand and more likely to be remembered it becomes easier to convince an audience of the validity of your approach and make them more likely to accept and take action based on your conclusions.

In the end, just think of the adage picture is worth a 1000 words, just like a good pie chart is worth 10,000 rows of excel data.

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 #1: Operational Analytics

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

By definition, a DSA professional uses 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.

Operational analytics is made up of all the analytics processes within an organization that take data and transforms the data into actionable intelligence. In short, this is management reporting.

Without a doubt the most widely used form of analytics, management reporting is deeply ingrained into the culture of data-driven organizations.

I often liken management reporting to a pyramid. The bottom of the pyramid is the data or the base of decision-making in an organization.

The middle of the pyramid is the processes of operational analytics. Where the data is transformed.

The top of the pyramid is the decision-making. Managers need intelligence that comes in the form of insights. Great analysts deliver these insights in reports, dashboards and visualizations.

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.