Seven Years in the Philippines

In January it will be seven years since I left Wells Fargo and moved to the Philippines to set up an analytics training company.

As year seven comes to a close, some reflection on how I got to where I am now would be beneficial to my strategic planning for the next seven plus years.

BPO Elite was my first venture and the idea was to train fresh graduates and young professionals to be analysts. It was a pretty successful first year in terms of developing a training approach to teaching the fundamentals of business analytics. Business wise we made a lot of missteps along the way that ended up dooming the business. But the training method was sound and I started to build up my credibility as an analytics experts in the Philippines.

Year One was all about validating that empowering people to be analysts was indeed something I could do successfully.

Year Two brought DMAIPH, Decision-Making, Analytics & Intelligence Philippines to life. Based on the business lessons learned from the shortcomings of BPO Elite I focused more on building an influencer network. Entering in to business deals where other people would market my trainings, freed me up to focus on meeting with influencers. The goal became to work within existing networks and expanding reach so that more and more people learned about the important of analytics with DMAI top of mind on how to train people to do it.

Year Two was the year I built the foundation that allowed me to become the top analytics training expert in the Philippines.

In 2014, I launched a separate business focused on the outsourcing of analytics and data heavy customer care solutions. For a large part of the year the analytics trainings took a back seat to setting up a team of 100 office and home-based staff for clients in the U.S. It wasn’t the reason why I moved to the Philippines, but the opportunity proved to be quite lucrative and allowed me to keep doing analytics trainings and speaking engagements without having to worry to much about that part of my business being profitable.

Year Three was all about doing what needed to be done to make a profit.

By 2015, the outsourcing business was running smoothly, and I was able to get back to doing a lot of partner trainings and public speaking engagements. I had the good fortune to now be one of the most sought-after public speakers on analytics in the region, speaking at schools, conferences, and tech event I was also able to start getting my message outside of Manila and being asked to do events across the country.

Year Four was the year where I my face (actually the credibility behind it) really started to sell.

2016 was a big year for DMAI. I published my first book, Putting Your Data to Work. My goal was to make a guidebook that Filipino professionals could use a both a companion to my trainings as well as a resource to convince decision-makers to invest in more training. I also upped my game with doing more public trainings and speaking at even bigger events. It was a very profitable and satisfying year.

Year Five was where I perfected training content and my public presentations. The book was really the lynchpin behind all that.

By 2017, I began calling what I do as more an advocacy than a business. I got involved in several large-scale analytics training initiatives not just in the Philippines, but across SE Asia. I helped found an association to further an analytics centric focus in the outsourcing industry and was even invited to give testimony before the Senate of the Philippines.

Year Six was where it all came together. I hit that sweet spot where I was really good at something I loved doing and I got well paid for it.

2018 could have easily been a redux of 2017. In fact, we started doing a lot of high paying in-house trainings, bigger and more successful public trainings and I was being invited to take part in all kinds of big picture initiatives across the region. But something changed. 2017 was the year where I had reached the mountain top. As I look back at 2018, I have accomplished everything I had set out to do back in 2012.

That said, I’m not done with the Philippines yet!

Already have 5 trainings booked for the first quarter of 2019. Including ones coming up in January and March. Here are the links to find out more:

https://www.sonicanalytics.com/data-analytics-20

https://www.sonicanalytics.com/data-analytics-30

I will always have a soft spot in my heart for my adopted home in the tropics as I also look to expand my trainings to where I spent much of my youth… the state of Florida. .

Will be laying some seeds the next several months and kick off my first trainings and speaking engagements in the Sunshine state early next year.

Let’s see where the next seven years of championing analytics takes me.

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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. 

 

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Finding the Right Data at the Right Time

Sir Conan Doyle’s famous fictional detective, Sherlock Holmes, couldn’t form any theories or draw any conclusions until he had sufficient data. Data is the basic building block of everything we do in analytics: the reports we build, the analysis we perform, the decisions we influence, and the optimizations we derive.

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Basil Rathbone as Sherlock Holmes

Several years ago I came across a book called the Accidental Analyst (*www.accidentalanalyst.com). The book opens with the questions, “Are you drowning in a sea of data? Would you like to take control of your data and analysis to quickly answer your business questions and make critical decisions? Do you want to confidentially present results and solutions to your managers, colleagues, clients and the public?”

Written by two Stanford professors, the book explores how and why people become good analysts and goes into detail about how to approach analytics successfully. After reading the book I was inspired to come up with a way to teach analytics to college students and fresh graduates.

The core of both the book and my program hinges on the ability of an analyst to find the right data at the right time. The authors suggested that identifying your data is where it all starts. Identifying exactly what you need to address whatever it is that you need to report.

Back at Wells Fargo, the single greatest attribute that I had that made me successful was my ability to size up how long it would take to deliver something. Knowing what data I would need, where I would find it and how long it would take to analyze it to come up with something useful made me somewhat of a wizard in the minds of the team.

Finding the right data at the right time requires one to first know ends and outs of their data. You have to know how the data is captured, where it is stored and how it makes its way to you. Knowing the data architecture in your business is the key.

So you have to get to know the people who know where your data comes from and how it gets there. Learn from them. Partner with them. Buy them doughnuts.

A couple of years ago I came across an analogy being used to describe data in a business. That of a data lake. A data lake is the living, breathing, evolving pool of all the data in a business. If you have a good data architecture, and you can navigate it fairly easily, then you have a data lake. Ideally, your business has data structured in such a way you can live off it. Data to a business is like water to living things… it sustains life

So once you have the lake mapped out, then you have to learn how to fish it. Knowing where the fish are biting is another key. Once you know what data you need, you have to know how to get to it quickly.

Business Intelligence tools help us here. As does coding languages to extract data from a database. These are your fishing tools. You have to practice using them to be good at getting the right data at the right time.

Another way to optimize your data search is to save your work. Of as I call it leave yourself breadcrumbs. Save the query. Cut and paste the code into a document and save it. Write down the steps. Whatever you need to do to replicate what you just did so you can do it again in the future without starting over from scratch.

So to recap, if you know data structure, you understand how data is stored and you leave yourself clues to do things faster next time.
Now the other part of the equation is knowing if the data you are using is the right data. Finding data quickly doesn’t do you any good if you bring back the wrong data.

So, how do you know if the data you are using is the right data to be using?
I can’t count the number of times I asked myself that question. In general, just about every new analysis or project or research or whatever it is you are using data for, you have to ask that question at some point.

Even data you have used a hundred times and comes from a highly trusted source needs to be scrutinized.

Now if you work with data every day in a familiar format, from the same source and with no changes to the data gathering and storage process you don’t have to spend much time validating it. Usually you will see problems when something just doesn’t look right when you are doing the analysis.

On the other hand, things get a whole lot trickier when you are using data from a source you don’t use often, or something has changed in the way the data is populated or if it’s the first time you are using the data.

When this happens, I have a few suggestions on how to validate the data.

  • First off, pull the data, do your analysis and draw some conclusions. If it passed the eye test and it feels ok to you, then your job is just to validate it.
  • One simple way to do this is pull the data again the exact same way to make sure you get the exact same data. Or change one parameter like the dates used in the query. See if that significantly alters the way the data looks and feels.
  • Another option is to have someone else do the same thing independently. See if they get the same results you do. You can also find someone who knows the data to look over your work to see if it makes sense to them.
  • Whatever you do, the best way to prevent publishing or using bad data is to involve someone else. Not always possible, I know, but it’s the best way to go.

Another suggestion is to (1) get the data, (2) do some analysis, and then (3) step away for a while. Come back to it with fresh eyes. Don’t let our minds play tricks on us by making us see what we want to see and not what is really there.

I have seen several articles showing research that most time doing data analysis is actually spent cleaning data. In a lot of businesses, the data lake has become a data swamp, clogged with bad or unusable data. As the % of unstructured data increases daily, it’s easy to see how data swamps have become the norm. Even the most robust data collection and mining can run afoul if the data is not trustworthy.

I can’t stress this enough. No matter how good you are at analysis, or what tool you are using to do the analysis, if you don’t have an understanding of what happens to the data before it gets to you then you are probably not drinking from a clean lake.

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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. 

 

Staying Current with Analytics

Every few months I devote a day to discover what the current trends in analytics are. I do this both to refresh the slides in my presentation and to refresh my mind to see what I may have missed.

The amount of literature out there on analytics continues to blossom at an amazing rate, making it a true challenge to stay well versed on what’s hot and what’s not. I read a new analytics themed book at least once a month and I follow dozens of blogs, web sites and social media groups. Being well versed on what is current in analytics is a key to success.

Every time I go to list the top 5 analytics trends, I find that some things change and some stay the same. Ever since I have been writing about analytics, data visualization is near the top. Business dashboards continue to be a big need. Business Intelligence (BI) tools evolve and new ones’ pop up, but Tableau continues to be a market leader.

That said, we are still squarely in an MS Excel dominated world. Upwards of 80% of Filipino professionals I recently surveyed still use Excel as their primary tool for data analysis. And even the ones who have dedicated BI tools, still use Excel for 75% of their analytics work.  The adoption of BI tools is trending upward, but the curve is still very step.

Another trend that has been on the upswing is how more and more data is now unstructured data. The discussion on what is unstructured data and how best to mine it and integrate it with structured data has really been at the forefront for a while now. Going from 80% structured to 90% unstructured in just a few short years as mankind generates unprecedented amounts of data not easily captured in a database every day.

As October 2018, if I had to pick 5 current trends in analytics to talk about it would be:
(1) How to Conduct Impactful Data Storytelling,
(2) The Analytics and Data Science Talent Shortage,
(3) Using Big Data Analytics for Digital Transformation,
(4) Optimizing Data Warehousing and Data Lakes,
(5) Which Tool Is Best; Tableau or Power BI, R vs Python, etc

And thats is not even touching topics that are on the cutting edge like machine learning, artificial intelligence and augmented analyst. Although those are super important to an overall understanding of how we can optimize data, these topics generally are several steps down the road from where my audience sits. They are still trying to master the fundamentals of business analytics and introductory data science.

So I spend a fair amount of time looking for YouTube videos or TED Talks  on these topics  to add to what i read.

The amount of information available to consume if immense. I guess as we have more and more data and more and more tools to analyze data, we will have more and more people writing about how to use data.

Its a fun time to be the Data Guy.

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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. 

From Putting Your Data to Work… A Basic Overview of Analytics

Analytics is about looking for patterns in data to help answer questions. Most businesses use analytics to help ensure more data-driven decision-making.

The primary people responsible for conducting analytics on the massive amounts of data we have today are analysts. Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly.

Many Analysts today feel like they are drowning in a sea of data. They need to know how to take control of their data and analysis to quickly answer business questions and make critical decisions. They want to confidently present results and solutions to their managers, colleagues and clients.

You should get started by building a baseline understanding of analytics. The term analytics can often be used interchangeably with statistics and data science. What separates analytics from disciplines like statistics and data science is generally the speed of the analysis and the focus on solving business problems.

The most common form of analytics is business analytics, which is usually used by senior leaders and decision-makers to investigate problems, validate assumptions and to guide strategic planning.

Business analysts are therefore the most common type of analyst. If you do a job search on the title analyst, as many as half the posting will likely be business analysts. However, analytics can be used in an almost limitless number of business functions in specific areas like HR, recruitment, marketing, finance, and so on. Each one can have its very own analyst.

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Analysts have been around a long time, but recent technological advances have both allowed us to produce and capture more data as well as give us the ability to analyze immense data sets quickly. Thus we are amidst a huge boom in the applications of analytics and the need for analytics talent across the globe. Analytics is something just about every business leader is trying to figure out how to use more effectively in their business. To add to our challenge, the demand for good analysts is booming just as fast as the explosion in big data.

As a result, there is a huge shortage of people who are skilled in working with data to answer questions and solve problems. This is why you have seen the number of analyst job postings increasing at an amazing rate.

If you are a business leader, manager, owner, and/or executive are not actively trying to surround yourself with analysts and if you are not infusing an analytics centric culture in your business, you will most likely soon see your business fail.

A business needs analysts to make sense of big data, manage the storage of the data, and know when to use which of the 4 types of analytics (descriptive, diagnostic, predictive, and prescriptive). To be effective, analysts need to have business intelligence tools to create data visualizations, build business dashboards and tell stories with data.

So whether you are an analyst or someone who oversees analysts, Putting Your Data to Work is designed as guidebook to help you get the most out of your business data.

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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.

Revisiting “My Analytics Story” for the upcoming 3rd Edition of Putting Your Data to Work

My Analytics Story
Analytics is in many ways a new profession and up until very recently few people have seen being an analyst as career path. In fact, the majority of analysts became so by accident. To understand analytics, the first thing you should know is that there is no one, right way to analyze things.
As with my case, most analysts are drawn to analytics because they like to solve problems, have an affinity for working with data, are tech savvy and above all else… insatiably curious. By the time I first had analyst in my title, I had already been doing analytics for several years.
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Before I was even out of college I became the “Data Guy. I found my novice skills with Excel, my interest in sharing knowledge and my ability to solve problems made me highly employable. Still, there is nothing specific in my background that would suggest I’d become an analytics expert someday.
I majored in History with a plan to be a teacher and even obtained my Master’s Degree in Education. After college I started to teach, but the school I was working at went bankrupt. So I took a job with Wells Fargo Bank just to pay the bills and 15 years later I had amassed a wide range of analytics skills.
If you ask anyone with analyst in their job title, most of them have similar stories. Until recently you could not even get a degree in analytics as schools are just now offering analytics focused courses and degrees.
In 1998, I had the good fortune of being hired by Wells Fargo. The factors that contributed most to my success with the bank were two things inherit in the culture; the progressive use of data in decision-making and the accepted practice of moving up the corporate ladder by moving between departments.
If I had to pick one thing above all others that had made me a good analyst, it is my ability to quickly assess a problem and then identify the data needed to solve the problem.  For me, finding the right data is the most important trait to have and also the hardest to teach. It comes out of being curious and letting that curiosity drive you to find answers.
For 15 years that drive lead me to add new skills, learn new technologies, and develop new methods to become a proverbial jack of all trades when it comes to analytics. I often describe myself as a super hero, curiosity being my super power and the wide range of skills I’ve picked up being items on my analytics utility belt.
I am far from an expert on most of the ever increasing number of analytics tools out there, but I know what they can do and what they are good at. There are definitely a lot of people who are better at different aspects of analytics and no one can know it all. But in the end, I have become in many ways a guru of analytics.
I love talking about the fundamentals of analytics, explaining it in layman’s terms, empowering people new to the concept. I also have a passion for sharing my experience with predictive analytics models, using SQL code to write a complex series of table joins between data sources or figuring out what tool would be best use to build a business dashboard.
For the past 7 years now I have been exploring data sets, answering questions, and providing solutions here in the Philippines and loving every minute of it. Analytics… it’s more fun in the Philippines! 🙂
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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. 

More and More Frequently I Find What I Do Being a Form of Data Evangelist

The concept of a key influencer in a field being called ad Evangelist has been around business for awhile. I remember reading how early on, called their marketing people evangelists. One the comes to mind is Guy Kawasaki, who wrote about this in his book Enchantment.

When you have something that is either new or still young in its overall adoption cycle, you need evangelists to raise awareness and being the process of acceptance.

When it comes to data evangelism, there has definitely been a number of key leaders pushing for more and more adoption of analytics across various organizations. Bernard Marr is one I have followed quite extensively.

Based on the importance so many companies have placed on analytics in recent years, you would expect to find that just about every business leader buys into the concept of using data to drive decision-making.

To be sure, the tech giants and the banks have been on board for a long time and you have seen the adoption of large-scale analytics really start to have a lasting impact among major players in fields like professional sports, the entertainment industry and politics.

And nowadays, most social media platforms have lots of built in analytics that provide instant insight into what’s hot and what’s not.

However, both factual evidence and general observation are showing this is not necessary the case across the board. We still see headlines saying things like “62% of businesses have no data analytics strategy”.

In fact, many small and medium sized companies are still not where they could be when it comes to optimizing their business data.

Three of the biggest challenges they face are not really knowing what question to ask, how to manage the data so that it is well governed and getting the data to decision-makers seamlessly.

Terms like data interpretation, data collection, data governance, and data automation are not concepts easily articulated by many business leaders.

Having a data intelligent business culture is a lot more than just buying a business intelligence tool and putting it on top of Excel.

There needs to be solid foundation in all aspects of the data life cycle, a clean and well governed data lake to house all business data, and the ability to present data impactfully.

I have found that this is often the missing element when organizations are trying to craft an analytics strategy. They focus on technology or they go out and acquire high priced talent, but in the end they struggle because not enough of their decision-makers are on the same page.

As I train groups of professionals, both in public and in in-house trainings, I find most of the attendees do not have a solid foundation in how data is collected, stored and managed. They just know how to run reports, build simple dashboards and share data in ways that do not often influence the audience as intended.

So that is what I have found myself doing hundreds of times the past several years. Helping build that foundation. Connecting the dots between the various phases of the data life cycle and helping define the data value chain. Once an organization has that down, then going out and getting a fancy new tool or bringing on data science makes sense.

Being a data evangelist is all about getting not just 1-2 executives to buy into the power of analytics, but making sure the whole organization is in a place where they can truly optimize their data, become more business intelligent and compete on the same level as the big boys when it comes to making data-driven decisions.

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DMAIPH – Decision-making, Analytics & Intelligence Philippines

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.

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. 

Data Storytelling That Really Works

Over the past year or two, there has been a huge buzz around data storytelling.

Like so many other buzzwords associated with analytics, people get caught up in the hype and think they have finally found the magic solution to putting their big data to work.

I have attended dozens of conferences and have frankly been underwhelmed by most of those out there talking about data storytelling like its rocket science that costs a lot to deliver.

I have also heard direct feedback from a number of companies who have privately complained that the high priced, high tech data storytelling trainings on the market do not meet their needs.

So, in response to these facts I have come up with my own training on data storytelling. Specifically tailored for the Filipino professional and full of hands on exercises that can be practically applied.

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This two-day workshop is currently only being offered as an in-house training. Please contact us through http://www.sonicanalytics.com to learn how to book us for Data Storytelling That Really Works.

SECTION ONE – Preparing Big Data for Storytelling

Successful storytelling starts with having clean, accessible and organized data. We will start with an overview of tips for good data governance.

SECTION TWO – Knowing Your KPIs

You have to narrow down your data elements into the ones most key to your business. We will conduct an exercise to help us boil down all the data we have into just the 2-3 key points we need for our story.

SECTION THREE – Storyboard Your Data Story

Before we get into designing any visuals, we need to think of about the flow of our story from end to end. Tale part in a classic storyboarding exercise just like they do at Disney.

SECTION FOUR – Using Business Intelligence Tools for Storytelling

There are many tools out there that we can use to facilitate storytelling. We will optimize the BI tools you have in house as well as free online tools to get the best bang for your buck.

SECTION FIVE – The Key Elements of Data Visualization

Most people just through together a bunch of charts and graphs. That rarely works well. Master the various types of data visuals so you always use the best visual to explain your data

SECTION SIX – Business Dashboards for Storytelling

At the core of your data story needs to be a venue for your audience to play with the data themselves. Learn how to design impactful dashboards and build a business dashboard prototype

SECTION SEVEN – Building the Narrative

For most analysts and data scientists, the hardest part is what to do with your data and analyze once you have it. Let me show you how to craft your data into a narrative that will truly influence your audience.

SECTION EIGHT – Delivering Impactful Data Stories

Now its time to bring it all together. Apply the key elements of data storytelling to make more compelling analysis and reporting.

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Dan Meyer heads Sonic Analytics, an analytics advocacy with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and has recently begun offering public training seminars in the United States.

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized organizations looking to enhance their data-driven decision-making capabilities. We also advocate the use of analytics for civic responsibility through training, consulting and education.

As citizens of this great democracy, we need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). This approach to a data savvy work force starts in school. So, we started an internship program to empower our youth to use Analytics, plan Strategy and Present their insights… ASP!

When not training current and future analysts, you can find Dan championing the use of analytics to empower data-driven citizenship. His latest causes include supporting a 3rd Party initiative called the Service America Movement — SAM (joinsam.org), a non-profit providing legal assistance for immigrants  known as RAICES and  (raicestexas.org) and Immigrant Families Together – an effort to unite immigrant families (www.facebook.com/ImmigrantFamiliesTogether).

Data Analytics 2.0: Data Management and Visualization – Sept 25-26 in Ortigas

WHEN: Sept 25-26, 2018, 2018 | 9:00AM – 5:00PM

WHERE:Crowne Plaza Manila Galleria

COURSE OVERVIEW: Analytics Expert Dan Meyer will be conducting a unique analytics training focusing on both Data Management and Visualization.

A presentation of the fundamental concepts and techniques in managing and presenting data for effective data-driven decision making.

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 four primary roles in analytics; data steward, data manager, data scientist and data analyst.
  4. 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:

  • Attendees will learn how to identify the right data, how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.
  • This training will also teach you variety of Data Visualization techniques using Tableau such as: heatmaps, and dashboards.
  • Alongside with Visualization, this training will also teach you how to present and tell story with your data.
  • Helping your managers, CEO, board of directors and even business owners make data-driven decisions.
  • 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

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
  • Learn how to tell a story using data and learn how to present it visually appealing.

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.
  • Academic Institution: Faculty Members, Research, Professors, Etc. who wish to further their knowledge in the area of Analytics (most especially Business Analytics).
  • Professionals who are looking into upskilling themselves in Analytics.
  • HR and Finance Professionals who are managing huge amount of data.

KEY TOPICS: DAY ONE – MANAGING DATA

SECTION ONE – Data Collection, Storage and Governance

  • Learn the process of gathering and measuring information on targeted variables to answer relevant questions and evaluate outcomes.

SECTION TWO – Data Driven Cultures

  • Per Gartner, “The data can only take an organization so far. The real drivers are the people.” We will assess your company’s culture.

SECTION THREE – Optimizing MS Excel

  • Most of us use MS Excel for the majority of the analytics, so learn some tips on how to optimize the use of the powerful tool.

SECTION FOUR –Data Preparation for Advanced Analytics

  • Learn why these 5 D’s are essential to data preparation for advanced analytics and data science.

KEY TOPICS: DAY TWO – PRESENTING DATA

SECTION FIVE – Business Intelligence Tools

  • Get hands on with using Tableau Public and find the right business intelligence tool for your business needs.

SECTION SIX – Data Visualization

  • Master the various types of data visuals so you always use the best visual to explain your data

SECTION SEVEN – Business Dashboards

  • Learn how to design impactful dashboards and build a business dashboard prototype

SECTION EIGHT – Data Storytelling

  • Apply the key elements of data storytelling to make more compelling analysis and reporting.

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Dan Meyer heads Sonic Analytics, an analytics advocacy with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and has recently begun offering public training seminars in the United States.

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized organizations looking to enhance their data-driven decision-making capabilities. We also advocate the use of analytics for civic responsibility through training, consulting and education.

As citizens of this great democracy, we need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). This approach to a data savvy work force starts in school. So, we started an internship program to empower our youth to use Analytics, plan Strategy and Present their insights… ASP!

Analytics Centric Cultures – Learn More June 5-7, 2018 in Ortigas

Inspired in part by Bernard Marr’s 2010 book, The Intelligent Company, my goal these past several years has been to build and/or be part of data-driven business cultures. The description of the book on Amazon sums it up well, “Today’s most successful companies are Intelligent Companies that use the best available data to inform their decision-making.”

In his book, Bernard advocates for using Evidence-Based Management that is using the best available data to inform decision-makers. In parallel to this, I have been empowering companies and professionals to empower decision-makers to use more data as well. I call it data-driven decision-making, but at their cores, there are very similar approaches to managing success.

The cornerstone of the book is the five steps to more intelligent decision-making, which are:

  • Step 1. More intelligent strategies — by identifying strategic priorities and agreeing your real information needs
  • Step 2. More intelligent data — by creating relevant and meaningful performance indicators and qualitative management information linked back to your strategic information needs
  • Step 3. More intelligent insights — by using good evidence to test and prove ideas and by analyzing the data to gain robust and reliable insights
  • Step 4. More intelligent communication — by creating informative and engaging management information packs and dashboards that provide the essential information, packaged in an easy-to-read way
  • Step 5. More intelligent decision-making — by fostering an evidence-based culture of turning information into actionable knowledge and real decisions.

As information and data volumes grow at explosive rates, the challenges of managing this information is turning into a losing battle for most companies. In the end they find themselves drowning in data while thirsting for insights. Combine this with an increasingly severe shortage of talent with analytics, data visualization and good communication skills, things look bleak for companies not adhering to lessons like those suggested in the Intelligent Company.

In addition, Data-Driven Cultures Do These Things:

  1. They embrace Big Data. They aren’t afraid of it. They relish the addition of new data sources and actively look for more.
  2. Managers use Evidence-Based Management techniques. Just about every choice comes based on data analysis.
  3. Challenges are addressed with Data. When something happens that was unexpected, the challenge is met with a data centric approach.
  4. The right data is being used. A lot of work goes into validating data and keeping it clean and fresh. The concept of having a data lake that supports multiple parts of the business is in place.
  5. They have the right analytics talent. Analysts are empowered to go out and discover not just current challenges, but look for potential ones as well.
  6. They know how to communicate. The sharing of information is done to benefit everyone. You won’t see lots of data trapped in silos. Data has no one true owner.
  7. They take action based on their data and analysis. You don’t see a lot of useless reports that kills a small forest or clog up an inbox with massive files. They keep it smart and simple.

Data-Driven cultures are a lot harder to find than they should be. In this day and age, every company should have a strategy on how to use data to drive more intelligent decisions, but they don’t. Success eludes many companies because they don’t have the 7 qualities listed above in place. If you were to ask what they look like it would be something akin to this:

· Top management is afraid of data. Senior leaders don’t even know how to use MS Excel. There is no analytics champion in the organization to spearhead data projects.

· Decisions are made based on what worked in the past, relying on experience and gut feel. There is little evidence used to go in any certain direction.

· When things don’t work out, data and analysts take the blame. You will hear a lot of “why didn’t you tell me” and “I didn’t see it coming” excuses.

· What data is being used is old, dirty, incomplete, full of errors and doesn’t tell the whole story. Reports are basically useless and just produced to look at what people generally already know. They look for what’s there, oblivious to what’s not.

· They do not share data. They hoard it. They don’t trust anyone else with access to it. The data is stored in unconnected storage places. There is no common understanding how to use data.

· They fail a lot. Success generally happens by hard work as much as luck. It’s impossible to know for sure what caused what to happen.

It’s not easy to take a company that has little or no data-driven decision-making and turn it into an Intelligent Company, but it can be done. I have done it. I have guided transitions from the stone-age to the information age. Let me show you how.

I will cover all these concepts in more in upcoming my training class on June 5-7, 2018 at Discovery Suites in Ortigas. For a list of training events, please visit www.sonicanalytics.com

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.