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. 

 

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The Hardest Part of Training Analysts? Fitting the Content to fit the Clock

I get asked a lot about what is the hardest part of teaching people to use analytics and training analysts.

The biggest challenge is really trying to fit content into a timeline.

Analytics is not something you can box up an mass train on.

That’s why so many analytics training approaches fail.

Trainers are forced to either spend too much time on a few parts of analytics or spend too little time on a lot of important concepts.

It is really more art than science when it comes to using analytics because every data source is unique, every analyst has their own individual background, and every business question has a distinct answer.

Take a recent talk I gave at an event for HR professionals covering topics related to Compensation and Benefits.

I had 60 minutes to really introduce an audience of over 200 to analytics knowing they are generally unfamiliar with analytics terminology and mostly just use excel for basic reporting and analysis.

Before getting to a case study full of analytics jargon, I spent a few minutes given an extremely high level of some of the key concepts they need to now to fully related to the case study.

Here is a key slide:

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I then went into a 3 minute cruise at 30,000 feet over the landscape that is analytics.

Did my best to make sure the audience was able at the very least attach a definition and an example to each of the concepts.

Later on in the presentation, I wanted to leave the audience with some guidance on how to solve CompenBen questions with analytics, so I walked them through this slide:

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Based on lessons from my book, Putting Your Data to Work, I covered six steps for them to take back to work the next day.

If you are interested in owning your own copy of the book, please check out this link https://www.sonicanalytics.com/analytics-book

One of the reasons I have been so successful in my 7 years here in the Philippines, is that I am blessed with the ability to take some fairly complex and often intimidating concepts and turn them into tangible, layman friendly learnings.

If you are interested in learning more about how to attend a future public training on analytics or book me for a tailored in-house training designed specifically for your business, please contact me here or via my marketing partner, www.sonicanalytics.com 

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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 Key Ingredients of Impactful Analytics Trainings – Plan Your 2019 Analytics Trainings Now

When I first started conducting analytics trainings in the Philippines back in 2012, I was pretty much the only game in town.

There were very few companies offering any kind of big data management training, the terms data scientist and data storytelling were not part of the lexicon and 90+% of companies operating in the Philippines were pretty much just using MS Excel for their analysis and reporting.

You want to know what has changed in the past six years?

Not much, except that there are now at least a dozen companies offering analytics themed trainings, courses and certifications.

Sure they all sound like they are going to teach you cutting edge techniques to finally get a handle on all your big data, but in the end I keep hearing the same thing… the training I went to didn’t really give me anything I can use.

The training was too abstract, to high level, to dependent on one type of software, etc are the constant feedback I here from executives and managers who have been spending on outside training for their teams.

That plus it’s gotten quite expensive.

Analytics Executive Masterclasses, Big Data Boot Camps, Master’s Degrees in Data Science… they cost a lot when most companies are having to tighten their training budgets.

So the risk of wasting time and money on something that is not really going to move the needle is becoming a problem with all these analytics trainings.

With all the efforts of so many people to “help” the Filipino people level up their organizations analytics talent, you’d think by now we should be really competent when it comes to the use of advanced analytics techniques.

Unfortunately, that is just not been the case. There are definitely some pockets here and there were some world class analytics is happening, but for the most part we have to accept the reality that we have a long way to go to be on the level of Singapore, Viet Nam or China when it comes to analytics.

The one thing that has no changed at all since I started all this back in 2012, is the fact that most companies are still relying mostly on MS Excel for 90+% of their analytics.

Everyone wanted to run before they could walk. They through money at high priced trainings with cool sounding names promising to supercharge your business.

I think it’s time to face the reality, that while a few of our companies can do the big stuff, they are also sucking up all the available talent. It’s really, really hard to build a solid analytics team in your business without breaking the bank.

Unless you do what I do.

Get back to the basics.

Make sure everyone is able to really optimize the use of Excel.

Build a solid foundation in analytics that starts with aligning the data gathers, data managers, analysis builders and data presenters.

Make sure your dats is clean, easy to access, fresh, and shared.

Focus on what’s most important to the business.

Then you add on.

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So when you go out to find an analytics training for your team, look for some basic ingredients.

The 4 Key Content Ingredients to Analytics Training are:

  1. Data Sourcing
  2. Data Management
  3. Data Analysis
  4. Data Presentation

If its missing one or more of these ingredients, the training is going to leave you with a sense that something is missing. You will likely struggle to implement what you learned in class.

The 3 Key Trainer Ingredients to Analytics Training are:

  1. Knowledge
  2. Engagement
  3. Hands on Practice

 

Over the next couple of weeks I’ll be blogging about each of these ingredients, so that we you and your team sit down to plan your analytics upskill strategy for 2019 you’ve got all the angles covered.

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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.

Dan Meyer Quotes 2

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.

Finding the Right Data

“Data! Data! Data! I can’t make bricks without clay!”

-Sir Arthur Conan Doyle

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.

Finding the Right Data at the Right Time

Back at Wells Fargo, the single greatest attribute 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 few 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.

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.

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.

In the end, whatever you do, make sure you have the right data.

I will cover all these concepts in more in upcoming my training classes. For a list of training events, please visit www.sonicanalytics.com

I’ll be conducting the following business analytics trainings over the next few months:

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

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.

What is Business Analytics? In Most Cases It’s Simply Excel & 3 Bullet Points

Business Analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight, discover opportunities and/or drive business planning. *https://en.wikipedia.org/wiki/Analytics

The most common form of analytics is business analytics that are generally 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.

I was a business analyst for a large part of my career at Wells Fargo, but even before I had analyst in my title I was heavily involved in business analysis. Why?

Because I know how to use Excel.

It’s amazing how many people are scared of Excel. To many highly educated and successful business leaders across Corporate America, making a pivot table in Excel is like magic.

If you were able to take an honest survey of managers and supervisors across the country (world actually), you would probably be quite surprised by the high percentage who would prefer to find someone else to analyze their data.

That’s one of the biggest reasons business analysts are so prevalent.

Another is time.

I had a boss at one point that grilled into me the philosophy that no matter how much data you have, and how complex the analysis, it’s all worthless if you can’t boil it down to 2–3 bullet points.

That’s all he had time for.

3 Bullet Points!

So being a successful business analyst really require 2 skills; Excel and condensing data into 3 bullet points.

If you can do that, you’ll go far.

I did.

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 and build business dashboards.

I will cover all these concepts in more in upcoming my training classes. For a list of training events, please visit www.sonicanalytics.com

I’ll be conducting the following business analytics trainings over the next few months:

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

· September 4, Rancho Cucamonga (North of Los Angeles, US)

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.

Getting Started With Analytics

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.

A general definition of an analyst is a person who analyzes or who is skilled in analysis. Analysts examine things carefully and in detail so as to identify causes, key factors, possible results, etc. generally using a process of identifying, inventorying and integrating data. *http://www.dictionary.com/analyst

I often hear that most 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 most likely clicked to this page because you fit the description above. If that is the case, then you made a good decision. 😉

All kidding aside, I have designed a method to help you look at analytics in a way that will make data and analysis easier to understand and conduct. My trainings and published content will also instruct you on how to share data in a more dynamic and influential way.

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. In fact the quickening demand for analytics talent has made it very hard for most businesses to find good analysts.

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.

Keep in mind that 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. Do you have analysts on your team?

Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly. Are you an analyst yourself?

If you answered yes to either question, but you feel you need more training for yourself or your team, you are not alone.

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 and build business dashboards.

I will cover all these concepts in more in upcoming my training classes. The classes are designed specifcally for people new to analytics and for business leaders looking to upgrade the level of analytics in their business.

For a list of training events, please visit www.sonicanalytics.com

Upcoming Training Dates

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 14, Rancho Cucamonga (North of Los Angeles, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

My goal with this series is to help you look at analytics in a way that will make data and analysis easier to understand and conduct.

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.

DATA Analytics 3.0: Big Data, Data Value Chain and Data Visualization with Tableau – February 20-22, 2018

DMAIPH is proud to present this 3-day Data Analytics training that covers different aspects of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, SQL and in depth learning of the tool “Tableau”, this is also designed for those with little to no prior experience with these tools.

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

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.

 

LEARNING SESSION OBJECTIVES:

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

 

IN THIS SESSION, YOUR ORGANIZATION WILL BE ABLE TO USE:

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

 

IN THIS SESSION, YOUR PARTICIPANTS WILL BE ABLE TO:

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

 

WHO SHOULD ATTEND:

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

 

Continue reading “DATA Analytics 3.0: Big Data, Data Value Chain and Data Visualization with Tableau – February 20-22, 2018”