My Superhero Origin Story

My superhero origin story started against the backdrop of the 2008–2009 Financial Crisis. Let me explain a short history here, so stick with me. During the financial crisis, there was a bank that went bankrupt called Wachovia. If you are not aware of Wachovia, they were a bank that started on the East Coast and over time they spread westward, while Wells Fargo started in California and moved eastward. Wells Fargo was one of the few banks that was able to wither the financial crisis pretty solidly and when Wells Fargo acquired Wachovia, it was a pretty big deal for a number of reasons.

We did money transfers aka remittances, where people send money from the US to family and loved ones overseas. It is quite common for people that come to the US to work or to live still have family overseas, that they are responsible for. To support them, they sent money back to help pay for things like their parents’ retirement, or to help their brother or sister set up a business, or they are paying for their nieces and nephews’ education… whatever it may be. This is a big business; in fact, Wells Fargo had a goal of trying to get towards the top of that industry.

Our sights were clearly set on Western Union, being the market leader, and we put a lot of resources into the soon to be converted Wachovia branches in Florida. The goal within the bank, within my team, was to be able to get me number two one the merger was final. We would pass MoneyGram, pass, all the other money transfer operators and put Wells Fargo up there, right behind Western Union.

Now I don’t say that to brag, but around the same time this merger was happening, I realized that I was different. I had a level of skill that set me apart from most of the other analysts working at Wells Fargo during my tenure. This skill, which I had progressively been developing over the year, was my ability to take large, complex data sets from a variety of sources and blend them together to see trends and patterns that most analysts would likely miss.

Like with any superhero origin, when faced with a big challenge, a new power emerges that empowers the hero to save the day. And that’s exactly what happened.

Getting back to Wachovia and Wells Fargo, Wachovia was a diversified financial services company based in Charlotte, North Carolina. Before its acquisition by Wells Fargo and Company in 2008, Wachovia was the fourth-largest bank holding company in the United States, based on total assets. The acquisition of Wachovia by Wells Fargo was completed on December 31, 2008, after a government-forced sale to avoid Wachovia’s failure. The Wachovia brand was absorbed into the Wells Fargo brand in a process that lasted three years. source

This was a pretty big deal, because Wells Fargo up into that point did not have branches in the state of Florida. Wells Fargo had never set up shop in Florida, which is a very diverse state, with a lot of immigrants and first-generation citizens who send money to families abroad.

People who are likely to send money back to their homeland, or to their country their parents came from, and so when they do that that is a great opportunity for Wells Fargo. As the Wachovia branches were rebranded as Wells Fargo, we could use them to send our money transfer service. In fact, we would be the first bank in Florida to be able to send money through a bank which would give the customers have much better benefit than sending through a money transfer service.

Needless to say, everyone was excited. As we finalized marketing plans, I was in a staff meeting and we were talking about what we were going to do when we are able to finally have rebranded stores. We were ready to acquire tens of thousands of new customers and sign them up for the Express Send Service. With this huge opportunity in front of us, the marketing meeting, was about the plans for the launch of the remittance product in Florida.

The marketing team had a whole bunch of events planned, our communications strategy was shared, and we picked a rebranded store in Miami, where we were going to have a ribbon-cutting ceremony. Our plan included inviting local dignitaries the local news, etc; was expected to to make a big splash. We are going to launch in Miami, and on the surface, it made sense because Miami is the biggest city of Florida. The city’s population has incredibly high percentage of immigrants and first-generation Americans, our key target.

However, what I thought in my head, as we are going through all this stuff in the media was that most of the people that have migrated to Florida come from countries that Wells Fargo has not traditionally sent money to. Now, take a step back remember, I said Wells Fargo was a west coast centric bank, most of the money that Wachovia customers send overseas goes to places around the Pacific, China India the Philippines and Mexico.

In addition, we had pretty big markets in Central America like El Salvador, Guatemala. That is where our sweet spot had been for the past several years. Wachovia is East Coast centric; their branches are in parts of country where a lot of people that migrated to the US don’t come from the same markets they do in the West Coast. They come from the Caribbean, they come from South America…. i.e. Colombia, Venezuela, Puerto Rico, Cuba, Dominican Republic, and Haiti. This population of remitters was not one that Wells Fargo had a lot of history sending money to. Here we are excited about sending money overseas, about helping our employee, our customers, be able to send money to their loved ones and yet I’m thinking we have a problem.

Long story short, this is an issue for me because I looked at the data in my head. What I have known previously about the demographics of the area and populations in the state of Florida. Because being a data guy, I know a lot about the graphic data and geographical distribution of our customer base and the digital customers.

So, I raised my hand, I explained to everyone in the meeting, exactly what I just shared with you. The whole thing about, Miami not being the best place to launch in Florida, that its somewhere where we are not going to have a big turnout of new customers. I added that because we are not traditionally sending money to their home countries, this entire plan will fall flat.

I expected that to be enough. The data spoke for itself.

However, everyone was kind of like “well yeah that makes sense Daniel, but you know we’re locked in we’re still going ahead with Miami”.

Basically, I got out voted.

It was time to find a phone booth and put on my cape.

Daniel Meyer heads Sonic Analytics, an analytics firm with offices in Manila, the San Francisco Bay Area and Ocala, FL. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and offers big data coaching and analytics training seminars on both sides of the Pacific. Dan has also recently joined the Powerteam International family as a small business analytics resource speaker.

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 by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in STEAM 2020 Conference.

Best Advice Ever For a Newbie Data Scientist

“Data is hard to come by… so your goal should be to come across as the kind of data science-obsessed lunatic who will build your own goddamn dataset if that’s what it takes to get the job done.”

The above quote by Jeremie Harris of towardsdatascience.com is from his article: https://towardsdatascience.com/the-economics-of-getting-hired-as-a-data-scientist-e3882933b43c

It is probably the best advice I have ever come across by an aspiring data scientist.

As I tour around SE Asia and the United States talking about big data, A.I. and other geek stuff, I get asked quite often, “What skills do I need to be a data scientist.” People expect me to rattle off a series of apps, languages and programs that will help them get a good data science job. And I do often recommend they learn Python, Tableau, SQL etc.

However, my first bit of advice is to study the employer you want to work for. Find out what they need. Get curious so when you connect with the decision-makers and prepare for your interview make sure you know what you can do to help them.

Jeremie’s advice goes one better. Don’t just come ready to solve a problem, bring data with you.

The market has a lot of people trying to get started in data science so on the surface it can seem like a seller’s market. So many candidattes have a sense that they can just present themselves, their education and their skills on a piece of paper or with some kind of theoretical construct and people will be dying to hire them.

As W. Edwards Deming famously said, “In God We Trust, All Others Must Bring Data”.

Literally, apply that to your job search and I’d definitely be impressed.

Daniel Meyer heads Sonic Analytics, an analytics firm with offices in Manila, the San Francisco Bay Area and as of February 2019, Ocala, FL. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and offers big data coaching and analytics training seminars on both sides of the Pacific. Dan has also recently joined the Powerteam International family as a small business analytics resource speaker.

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 by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in STEAM 2020 Conference.

The 3 Pillars of Small Business Analytics

When I consult with small business owners, there are 3 areas where my guidance generally has the most impact. I call these areas the 3 Pillars of Small Business Analytics.

The first pillar is a Competitive Landscape. I have found that very few small business owners really have a handle on the competition.

A competitive landscape analysis will reveal threats and opportunities that generally are not obvious to a business owner who focuses most of his/her energy on running the business itself.

Some of the data points you can capture and analyze include pricing, location, business size, quality, scope of business, diversity of product offering and of course revenue. You would be surprised to find how easy it is to gather all this info.

Knowing where your products and services stack up against your competition is a key to prosperity. To achieve this understanding you need to use analytics.

The second pillar is a Demographic Profile. I have also found that very few small business owners really understand the demographics around their business.

A demographic profile analysis will illustrate how closely your customer base mirrors the actual population around your business. In many cases small businesses are not positioning their services correctly based on the opportunity in their market.

Data to include would be traditional demographic markers like age, race, sex, family status, financial status, economic state, etc. There is a ridiculous amount of data on the internet that can be mined free and easy.

Making sure your business is properly positioned to take advantage of your arket will ensure more long term success. The data is out there; you just need to know how to bring it into your analytics process.

The third pillar is Customer Insights. With the boom in social media, most small businesses have not figured out how to capture and analyze all the information being published and shared about their business.

Customer Insight analysis allows a business owner to stay on top of problems and identify how customers feel about their business quickly.

We all know how quickly things can go viral and having a good tool to capture customer sentiment in social media is generally the most overlooked aspect of running a small business.

Positive and negative reviews, trending items, number of likes, follows and shares, are all items that can be rolled into customer insights. You can combine this with surveys, focus groups and loyalty programs among other things to get a full picture of your business.

If you are a small business owner, decision-maker or analyst then focusing on these analytics pillars will make all the difference in the world.

And the best part, is they are all free and easy to bring into your business.

Small Business Analytics — The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. Sonic Analytics is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact us now at info@sonicanalytics.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

Dan Meyer heads Sonic Analytics, an analytics advocacy with offices in Manila, the San Francisco Bay Area and as of February 2019, Ocala, FL. 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 by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in Data + Science Program and the Data + Women of Tampa Meet Up Group.

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”

The Analytics Puzzle for Higher Education in the Philippines

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

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

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

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

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

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

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

And that is exactly why I started Augment BPO.

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Augment BPO. The Augment BPO Data Science and Analytics Advocacy Project (Augment BPO) is empowering BPO Companies, Executives, and Workers in the Philippines to prepare for and address the clear and present danger posed by Artificial Intelligence Chatbots (AI Chatbots) to BPO revenue growth and jobs through Data Science and Analytics strategy planning, awareness building and upskill training.

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DMAIPH Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Asia Pacific Economic Cooperation’s Project DARE initative, DMAIPH champions the use of using data. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in data science and analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

Top 5 Reasons to Attend the Digital Transformation Summit 2017

From the Global Chamber® Manila Newsletter

May 9, 2017

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

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

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

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

Become a Data Science & Analytics Pro! Apply for the DMAIPH Apprenticeship Program

A standard definition of Apprenticeship is a kind of job training that involves following and studying a master of the trade on the job instead of in school.

Learning to become an analyst for the most part has been something done on the job.  after working in a company and gaining subject matter expertise, those who had good analytics skills often found themselves going down the analyst career path.

Big Data and technological advancements in analytics processing and data science have changed all that.

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Nowadays, there are so many analyst jobs available that the natural order of learning to become an analyst isn’t working fast enough.

Higher education is trying to come up with solutions to offer analytics themed course, a few are already in place. But that’s only training 100’s when industry needs 1,000’s.

SO, to help fill the skills gap between the very finite supply of Data Science and Analytics (DSA) talent and the huge demand in the form of open jobs, we have to get outside the box.

You will see a lot more ideas like the DMAIPH Data Science & Analytics Apprenticeship program coming in the near term.

But don’t wait for the future, get ahead of the game.

Learn the DSA skills you need for a long and profitable career as an analyst.

E-mail me your resume today if you would like to learn more.  danmeyer@dmaiph.com

I will be taking on a few more apprentices in the coming months as we grow the program to implement APEC’s Project DARE recommended approach to gaining a basic understanding of what it means to be a DSA professional.

Hope to hear from you soon!

Dan

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Analytics Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience.

If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

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

How to master big data analytics and data management?

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

2-day Class: Big Data Analytics and Data Management

June 27-28, 2017

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

9AM-5PM

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

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

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

Learning Session Description

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

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

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

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

Learning Session Objectives

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

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

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

In this session, your participants will be able to:

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

Who Should Attend

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

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

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

Section Two – Assess Your Current Analytics Culture

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

Section Three – Using Business Intelligence Tools

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

Section Four – Interpreting Your Data and Analysis

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

Section Five: Presenting the Data Value Chain and Databases

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

Section Six: Data Processing with SQL

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

Section Seven: Accessing SQL Tables with Excel

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

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

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

Minimum Hardware and Software Requirements.

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

Case Studies and Exercises

Dan and Doc will use case studies and group exercises throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

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Learning Investment for 2-day Seminar:

Exclusive Offer!!

Early Bird Rate

P 12,000.00 + VAT

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

Group Rate (Minimum of 5)

P13,000.00 + VAT

Regular Rate:

P 14,600.00 + Vat

(starting April 21, 2017)

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

ABOUT THE SPEAKERS

Dominic Ligot, Data Scientist

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

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

Daniel Meyer, Analytics Champion

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

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

Reserve your seat here >>>

 

Data Science Philippines – Feb 2017 Meet Up

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

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

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

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

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

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

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Image from Forbes Magazine. 

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

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

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

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

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

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Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Data Science Philippines Meetup Group, DMAIPH champions the use of using data. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses.

We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.