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”

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Global Demand for Analytics and Data Science Talent

There are not enough analytics experts and data scientists to go around.

I say this a lot.

Just did a quick google search to put some recent data points and commentary to back up what I say.

The mass adoption of big data has seen companies across sectors scramble to hire enough data scientists to glean insights and drive decision making.

A decade ago, explaining data science to employers was challenging. Few people understood the value of a skill set that combines computer science, statistics, operations research, engineering, business insights and strategy and the impact it can have on a business.

But things have changed over the last five years. Not only has the term “data science” become commonplace, but data scientists have become highly sought after in the marketplace

According to a 2015 MIT Sloan Management Review, 40 percent of the companies surveyed were struggling to find and retain the data analytics talent. And the picture is starting to look even bleaker.

International Data Corporation (IDC) predicts a need by 2018 for 181,000 people with deep analytical skills, and a requirement five times that number for jobs with the need for data management and interpretation skills.

A report by McKinsey & Company is frequently referenced, stating that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

Deloitte’s Analytics Trends 2016 report notes that while there is a rising number of university analytics and data science programs (more than 100 just in the U.S.), they nonetheless can’t crank out enough sufficiently trained people to meet demand.

Consequently, the report recommends that companies should:

  • Actively recruit on campuses with data analytics programs.
  • Develop internships and student projects both as a recruiting tool and to groom students for an efficient transition to the general business world and company culture.
  • Establish meaningful and rewarding career paths with an infrastructure in place most likely to interest and attract new talent.

In a recent blog post, Facebook listed a number of tips for students to prepare for such fields. Chief among them: “Take all the math you can possibly take,” including probability and statistics. (And while you’re at it, the company recommends, make sure you take some computer science, and try to squeeze in engineering, economics, philosophy of knowledge, and the latest brain research, too.)

One of the reasons I am so bullish about 2017, is that appetite for analytics and datas science is through the roof. Finally, everyone is starting to get serious about how to infuse their decision-making with more data.

DMAIPH specializes in empowering and enabling leaders, managers, professionals and students with a mastery of analytics fundamentals. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out what we can do to help you acquire the analytics mastery you and your organization need to be successful in today’s data-driven global marketplace.

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Sources

http://www.business.com/recruiting/big-data-big-problem-coping-with-shortage-of-talent-in-data-analysis/

https://techcrunch.com/2015/12/31/how-to-stem-the-global-shortage-of-data-scientists/

https://content.pivotal.io/blog/mckinsey-report-highlights-the-impending-data-scientist-shortage

http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation

https://code.facebook.com/posts/384869298519962/artificial-intelligence-revealed/

 

 

 

Writing About Analytics

Writing about analytics is a great way for me to both share my passion and empower people to use more analytics.

It is amazing to me that it is mostly just the big companies investing in data-driven decision-making. The perceived difficulty and cost scare away a lot of small businesses. Nothing could be further from the truth. There are so many cheap or even free analytics applications and software packages out there.

I love to write about the various technologies available to people new to using analytics. I can take some pretty complicated stuff and make it seem much more palatable.

It is also common for older, more established companies that are run in a rather old school way feel that analytics is just too complicated and is probably just a fad that will pass. But harnessing big data (and small data) in and around the business can make the world a easier place to do business in.

I really enjoy sharing some simple techniques and methodologies that even the most old school business owners and leaders can understand. Sometimes they need to see it in a book to really get their heads around it.

Not having people in positions of influence who get analytics is a big problem for a lot of companies. As is not having the right level to talent needed to assure a successful use of analytics. The talent part of analytics is often the hardest part.

So I focus much of my energy on empowering students and young professionals to embrace the various analytics technologies and techniques out there to learn. The need for analytics talent continues to boom. So that is what I write about most.

Being an author, a blogger, a public speaker and a subject matter expert on analytics is simply what I was born to do.

So I keep writing. Everyday I write and blog and speak and share about taking data, analyzing it and presenting it in a way to can positively impact decision-making.

 

 

Q18: Can you please talk about recent developments in higher education on how to train more analysts?

The past couple of years have seen some remarkable developments in higher education in regards to analytics. Just a few years ago there were only a handful of colleges and universities in the U.S. that offered any kind of degree in something akin to data science. However, now you can find dozens of schools offering graduate degrees in analytics and/or data science. These changes in higher ed were preceded by several vocational schools and certificate programs. All in, if you do a google search on data science or analytics degree program you will get 100’s of schools in your results.

Besides the U.S., I have seen a few program in the UK and several in India getting more into analytics education. In the Philippines several schools have already started implementing the CHED (Commission on Higher Education) memo requiring schools to offer a business analytics elective series of classes. We have come a long way in a short time, but what is best for you?

If you are thinking about getting some formal education you will need to determine where you are currently with your analytics skills and where you want to be long term. Because of the crazy growth in the field, it can be pretty hard to tell what is the best bang for your buck.

Without pointing to any specific institution or program, I can give you some broad difference to consider. In a latter blog I will actually review some of the best programs and talk about them in on my blog site.

So here are the differences as I see them:

  1. Accidental Analysts. People who are doing a lot of analytics and have for some time, but have no formal training in analytics. These are accidental analysts who still make up a huge % of people doing analytics every day. For people at this level, going back to school full time to get a formal degree is not generally an option. For people in this bracket short term training programs and certifications in specific tools are the best bet to stay on the cutting edge.
  2. Legitimate Data Scientists. Few and far between, people with both the academic credentials and the business experience to do significant data science generally look upwards to getting a masters or even doctorate in a specialized field from a top school. There are a lot of programs out there to do that, but they tend to be pretty expensive and difficult to get into.
  3. Aspiring Data Scientists. If you are still young in your career and/or not finished with college you can consider getting your undergraduate degree in a related field and then progressing on to post graduate work. This is a recent development that poses an opportunity to those just starting out. In the near future these kinds of analysts will replace the accidental analysts for the most part. That is if there are ever enough.
  4. Part Time Analysts. People who do analytics or are part of a data science team, but have already established a career path in a different discipline. For those like you, training programs and certifications abound. It is pretty easy to find one that fits your unique situation and give you the added data muscle you need in your job.
  5. Managers of Analysts. If you are not really the one doing the heavy data lifting, but have team members that do. You need to be able to understand them, but not all the things they do, then you might be looking for a more generalist overview of analytics. Trying to optimize your analytics business culture and lead big data projects are skills you might want to improve on. There are training programs popping up for this need as well.

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So where does this take higher education? Some schools and programs are very broad based and offer generalist solutions. Others are quite specific and are geared to producing specialists. Knowing which education option is best for you is the challenge.

Higher Education across the globe is evolving to incorporate more analytics and data science into its curriculums. The need is there and is growing at a break neck pace. Where we are now is lights years from where we were two years ago, but where we need to be is far down the road.

More on that next blog post. In the meantime, if you are trying to figure out how to up your analytics game, drop me a note and I’d be happy to help you figure out what path you should take.

What Kind Of Analyst Do You Want To Be?

“The main part of intellectual education is not the acquisition of facts but learning how to make facts live.” – Oliver Wendell Holmes

An ANALYST is a person who analyzes and is skilled in analysis. Business Analysts (BA) are required to find, analyze and report business data to support business optimization.

The job functions of an analyst very greatly from business to business and even within each business job functions can vary from analyst to analyst. However at their core, you will find that just about anyone with analyst in the title has several things in common.

Based on the book, the Accidental Analyst, four character traits that most analysts have are:

  • PASSION for helping people solve real problems
  • KNOWLEDGE of the business being analyzed
  • EXPOSURE to thinking analytically and problem solving tools
  • EXPERIENCE using data to solve problems

In addition most analysts have certain personality types:

  • reflective
  • intuitive
  • deep-thinkers
  • and able to make quick judgments

These findings show a consistency across analysts no matter if their focus in on reporting, analysis and/or research, if they are working with small structured data sets or volumes of unstructured big data or if they are actively working to optimize the business or just providing information.

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Per CHED some of the analytics jobs graduates of the program should be ready for:

  • Jr. Business Analyst
  • Operations Assistant
  • (Web) Site Analyst
  • Marketing Officer
  • Jr. Operations Analyst
  • Financial Analyst
  • Supply Chain Analyst
  • Human Resources Associate
  • Training Associate
  • Administrative Associate
  • Accounting Analyst
  • Quality Assurance Analyst
  • Facilities Associate
  • Planning/Budget Analyst
  • Insurance Analyst
  • Social Media Analyst
  • Virtual Assistant
  • Customer Service Rep
  • Finance Analyst
  • Accounts Payable Analyst
  • Travel Analyst
  • Expense Analyst
  • General Accounting Analyst

This list is hardly exhaustive. On a typical day on jobstreet.com you will see hundreds of job titles that includes analyst in the title.

So I guess the next question to ask is, “What kind of analytics and analyst jobs interest you the most? ”

The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities. DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

Training, Training, Training, There Is No Other Solution

The the longer I am here in the Philippines, working in the BPO industry, the clearer this concept becomes.

As of today, there are over 2,000 analyst jobs available on jobstreet.com.ph

If you take all the students enrolled in all the recently analytics centric courses imagine that wouldnt even fill up 1/4 of the open slots.

So when I saw this image…

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I’m immediately thinking this is where so many decision-makers continue to get it wrong… you HAVE to invest in training your own people and/or training near hires. If you keep trying to pirate someone, you are just making the problem worse.

You end up with a mix of undertrained (and undermotivated) lifers and job-hoppers ready to take off as soon as something that pays more comes along.

Five Things That I Ask My Leadership Team To Do

As our team continues to grow and the type of work continues to diversify, I have been reflecting a lot on the way we approach things. The way we influence those we work with, the words we choose to motivate each other and the commitment we demonstrate to ourselves, each other and our clients all have a huge impact on our success.

Leaders do more than manage. They inspire and empower. They also hold people accountable. Having worked with and for some great leaders over my career, these are the top five things I ask my leadership team to do.

  1. Do The Work. Nothing inspires others more than seeing a person in a position of authority work hard. Putting in the extra effort, making sacrifices and going above on beyond to bet things done. Excelling at what you do is the best way to get others to do the same.
  2. Sharing The Vision. I use the term sound like a broken record a lot… meaning you should share and share and share stories and ideas and dreams that give people a vision of where things are going. In this fractured world, so full of distractions, it’s really not possible overshare your vision.
  3. Carrot And Stick. I use this metaphor a lot to remind my team that we have to be equally well versed in both discipline and praise. That we need to balance being a good cop and a bad cop. Being fair and just, is in the end what all employees want from their leaders.
  4. Don’t just give directions. Explain why things are important. Looks for root causes and not just the symptoms. Take the extra time to write a more comprehensive email, or sit down and explain something a second time, or use visuals to re-enforce why we do what we do.
  5. No excuses. True leaders accept responsibility, hold themselves accountable for failures and offer up solutions to problems. Unsuccessful leaders offer explanations and excuses.

So as we kick into high gear with expansion plans, these are the things I will be doing, sharing, reminding, and educating my team about.

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

5 Strategies For Recruiting Analytics Talent

http://data-informed.com/5-strategies-recruiting-training-decision-science-talent

Came across the above mentioned article. It starts, “A career in decision sciences/analytics continues to be one of the sexiest jobs of the 21st century, but the supply of analytics talent threatens to limit the promise of decision sciences.

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A report by McKinsey and Company estimates a shortfall of 140,000 to 190,000 data scientists and 1.5 million managers who have the skills needed to use the insights to drive decisions. And Gartner predicts that by 2015, big data will create 4.4 million jobs globally.

Data scientists are in short supply, but the dearth of decision scientists – the rare breed that combines the interdisciplinary prowess of math, business, technology, behavioral sciences, and design thinking – is even more alarming. For this reason, there needs to be an increased emphasis on recruiting and training as opposed to relying on acquisition.” The writer then listed his 5 strategies for recruiting analytics talent.

I have a few variations on his top 5, here they are:
1. Destroy the Top Talent Only Comes From Top Schools Myth
2. Test For Curiosity and a Learning Mind Set
3. Appreciate an Inter-Disciplinary Perspective
4. Teach the Art of Asking Questions
5. Be Both Big Picture and Tiny Detail Kinds of Analysts

So basically what it boils down too, is that business don’t just need high-end, well-educated data scientists, they need lots of people who think like analysts.

That’s what I specialize in, I take people who are curious, regardless of their background and I train them to unleash their curiosity and empower then to use data to make decisions.

Hiring a data scientist is not really an option for most companies I work with, but hiring one of my trainees to work in their office or online for their business is a very good option.

The Philippines is Going Beast Mode! 2 of 3

ASEAN Demographics

Sharing my thoughts on some great Bloomberg visuals my good friend Justin Calderon used in a recent story he put together.

http://investvine.com/charts-outlining-the-philippines-economic-trajectory/

Beast Mode is an American Football term for a player who singlehandedly dominates a game. This is the second of three visuals I will breakdown and comment on.

This slide tells me so much. Based on this I am convinced that its time to revamp my plans for training fresh grads in analytics. Look at how much younger the Philippines is then its neighbors! Combine this remarkable demographic datapoint with other factors like the investment being made in the BPO/Call Center industry, the education system geared to produce American style English, and the size of the talent pool.

When you do that you see what I see, an amazing opportunity to be in the middle of all the training, skill building and mentoring that will be needed to prepare this population boom for the jobs of the next 10-20 years.

In the previous post, it was noted how quickly the Philippines economy is accelerating and here you see a snapshot of the future. There are still so many potential detractors and possible hindrances ahead, so you have to pay them mind. However, its data points like that, backed up by analysis and on the ground intelligence that have me convinced its time to go back and jump in!

13 Months in the Philippines – Lesson One – Finding the Right People

Lesson 1 – May 2012 – Finding the Right People

Makati, Metro Manila, Philippines

I took a couple of trips to the Philippines in early 2012 to lay the ground work before committing 100% to moving there lock, stock and barrel. When I was there, one of the things I did was set up some interviews for my first BPO Elite employee.

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Now don’t get me wrong, I ended up with an amazing employee who would become one of my best friends. But the process itself had some serious flaws. Let me break them down. And even though I have extensive experience in recruitment and hiring, I made many of the same mistakes in the process that most managers make. They put it on themselves to do it all, they are the only ones in on the decision-making, and they don’t really look at the available data to help them.

When recruiting. I found out the true power of LinkedIn. I networked with a couple dozen candidates, and narrowed it down to six to interview based on e-mail conversations before I left the US. When I arrived, I set up phone screenings with the six and ended up then conducting two final interviews. Pretty standard stuff and thanks to LinkedIn, all the candidates where qualified to be my very first employee, a recruitment specialist. However, I did all this myself. And even though I have partners and an assistant back in the US, I took it on myself. That’s lesson #1, you cant always do everything yourself. It takes up a lot of time and it makes others think you don’t need or want your help. Next time I do this, I need to delegate and be more inclusive.

The next thing I did wrong was that I didn’t have one of my partners interview with me. I based my decisions on my gut. Now as an analyst, I am kicking myself about this, but as a first time business owner… its a very common mistake. There is tons of data that shows that candidates hired after interviews with more then one person as much as a 100% chance to stick around longer than those interviewed solely by one person.

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The final lesson that comes to mind is that I didn’t do a very good job of understanding the data available when it comes up to the recruitment industry in the Philippines. After being there a while and gathering data and insights, I over paid, I over promised and I over recruited. I hired two, at way more than the market price and I gave them pretty favorable terms. All things that more research would have uncovered.

So In the end it worked out, I got a great candidate who stuck with me thru thick and thin. I just wish I would have hired me the analysts to do the prep work for me the business owner. Hehe!

Analytics Tool > LinkedIn > http://www.linkedin.com

Analytics Concept > Marketing Analytics > http://en.wikipedia.org/wiki/Marketing_analytics#Data_and_analytics

YouTube Resource > http://www.youtube.com/watch?v=6jDjeNJrN14&feature=share&list=PL7EC252B253873D5D

My Analytics Story – My passion is solving problems by bringing together the best talent, cutting edge technology and tried and true methodologies. DMAIPH is all about empowering people towards better Decision-Making through the use Analytics and business Intelligence. This is what I do best. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly for a free consultation about getting more analytics into your career and your business.