Staying Current with Analytics

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

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

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

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

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

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

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

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

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

Its a fun time to be the Data Guy.

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DMAIPH – Decision-making, Analytics & Intelligence Philppines

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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DMAIPH – Decision-making, Analytics & Intelligence Philppines

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

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

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

TRAINING IN DATA ANALYTICS

By Maureen Andrei Lepatan

INTRODUCTION

We create data everyday. How? We, especially in this generation spend many hours in accessing our social media accounts, doing online shopping, playing games, watching movies online. Part of our daily routine includes internet and technology. By doing so, all of our hobbies generate data that are captured in various places and in different ways.

Every time we post pictures on Instagram, rant something on Twitter and post our status and photos on Facebook, we create a lot of data. There is a corresponding data point every time we comment or like something online. Imagine how many data we can generate everyday if every person of this planet accesses online.The data become closer and closer to infinity. That is why the term “big data” was created.

 With that being said, data analytics is key to handle pool of data. Analytics is about searching for clues that will enable us to find answers to our problems. We find, we analyze and we present our data.

Primary people for conducting analytics are called analysts. The problem would be that they are overwhelmed by massive amount of data and have trouble to handle them properly.

In order to be effective, analysts should master effective and current business intelligence (BI) tools that could help them to interpret the data properly and guide the companies and businesses regarding their strategies and decision making processes.

I started having interest in dealing with data when I was 3rd year in college. Before, I was a Math person. I am the kind of person who likes challenging activities and work on complex subjects. In the pursuit of my Economics degree, I used a lot of data and created graphical representations in order to survive essay crises and  loads of research papers.

Somehow, economics has the same idea as data analytics which is to tell a story out of the representations. The difference lies upon the frequency of the usage of business intelligence tools in data analytics.

Why did I dive into data analytics? It fits my personality, hobbies and skill sets. I am curious in nature and love to learn new things.  I love editing videos, photos and creating infographics and graphical representations. And data analytics made me combine all of these hobbies in data analytics. It enables me to be creative, analytical and communicative all at once. There is no wrong and right approach. I can be my own self. As long as I get the right data, visualize and verbalize them well, I’m good to go.

Data analytics gave me a sense of purpose. I think in this generation, being an effective analytics talent is what the world needs. I do not mean to disregard other jobs. I just want to be realistic about the present and the future. More and more businesses will build their companies using online platforms requiring more data analytics talents. If businesses do not adapt to the demands of the society, they will most likely fail. As a student and future professional, I need to prepare for these changes. Although I have a background in dealing with data, I need to learn timely business intelligence tools and to train myself to be a better data storyteller.

DMAIPH can help analysts and aspiring individuals who want to learn data analytics. The company conducts trainings to help increase effective and efficient analysts in the Philippines and meet the demands of the society when it comes to data enthusiasts.

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EXPERIENCE

Last September 25 and 26, I attended the training of Sir Dan Meyer regarding Data Management and Data Visualization. In a span of two days, I was able to have an overview of how data analytics works and how to use business intelligence tools to tell a story. Moreover,  I was also assigned to tasks like to welcome the guests and to assist Sir Dan in helping the participants to use Tableau since I also need to fulfill my duties as a business analytics trainee.

At first, I was really intimidated with the participants when they introduced themselves. I never thought that the people whom I say “Good Morning/ Hello” to are CEOs and various kinds of analysts in their respective companies. This really reflects that the demand for analytics talents in the Philippines is greater than the supply. When I talked to some of them, they said that companies have sent them to have trainings with Sir Dan and some of them personally wanted to learn to help their companies.

Training people is really a must to adjust in this day and age. As time goes by, more and more data are generated and unstructured data gradually increase. If data continue to produce increments, the world needs more and more analysts to handle them. In the case of the Philippines, Excel still dominates the analytics industry and is used primarily by professionals to conduct data analysis despite the evolution of  business intelligence (BI) tools. On the second day of the training, the practical application of the concepts taught in Day One were applied. Sir Dan tackled about business intelligence tools, data visualization, business dashboards and data storytelling.

I have 5 major takeaways that I want to share with you:

  1. Data Visualization is just half the job. We need to interpret the data correctly and relay the information such that a grade school student can understand the story behind the data. This is in order to create an impact to various kinds of people and encourage decision-makers to make relevant changes in their businesses. Just be simple and precise!
  2. Learning data science and analytics is all about experimentation. We shall be ready for mistakes along the way. We must continuously attend trainings in order to guide us and persistently practice on our own to obtain mastery.
  3. Companies are enchanting because people like them and trust them. As part of a company, we want to reflect the enchantment our companies have to give to the customers. Without the right strategies to be enchanting, people will not believe us leading to a low profitability and a bad reputation. We can be enchanting as analysts if we can deliver the data persuasively and we can work well with other people.
  4. Being an effective data scientist is a combination of being mobile when it comes to changes in technology and being adaptable in dealing with people.
  5. There are three types of analytics which include descriptive, predictive and prescriptive. How do we use them properly? Descriptive analytics can be effectively utilized if we want to know what happened to have insights in present trends. For example, we want to know about the profits in each month from 2015-2017. Secondly, predictive analytics is used to develop projections and provide information what might happen in the future. Expected sales can be best represented by predictive analytics. Lastly, prescriptive analytics is used to know what to do. We can use this especially if we want to build a model out of multiple sources and include many variables.

DMAIPH: FIRST TRAINING, FIRST INTERNSHIP

DMAIPH really provided me a brand new experience. Although I love dealing with data and graphical representations before I become an intern, I felt more impactful when I started my training. I got to help the participants how to navigate Tableau and had to work with wonderful people.  I was able to apply what I learned in the past and at the same time acquire new skills that will be beneficial for me in the future. I look forward to the trainings and more involvement that I can get from the company.

So far, so good.

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ABOUT THE AUTHOR:

Maureen Lepatan is an Economics student in De La Salle University and currently a business analytics intern in DMAIPH. She has a passion in data analytics especially using business intelligence tools such as Tableau and Excel. She has an eagerness to learn data structures such as SQL.

 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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DMAIPH – Decision-making, Analytics & Intelligence Philippines

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

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

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

We will feature case studies of real Filipino run business, exercises based on actual analytics challenges being solved by Filipino analysts, and provide you with a copy of my book, Putting Your Data to Work, an analytics guidebook for the Filipino professional
Connect with us via our marketing partner, http://www.sonicanalytics.com to learn about upcoming analytics trainings and events.

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

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

This shortage is definitely acute here in the Philippines.

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


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


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

1. Is there a shortage of Data Scientists now?
2. How many “Data Scientists” are there , both in name and in function ?
3. What are the future prospects for Data Scientists?

 

The answer to the first question is a resounding YES!
  • LinkedIn Workforce Report for US (August 2018) says “Demand for data scientists is off the charts  … data science skills shortages are present in almost every large U.S. city. Nationally, we have a shortage of 151,717 people with data science skills.
  • Note that LinkedIn reports shortages for people with “Data Science Skills”, not necessarily people with “Data Scientist” title.
  • We can estimate the demand for “Data Scientists” from two popular job search sites – indeed and Glassdoor.
  • Search on indeed.com for “data scientist” (in quotes) in USA finds only about 4,800 jobs. However, in a search for data scientist without quotes, about 30,000 jobs.
US is the largest but not the only market for Data Scientists. We can also see strong demand for Data Scientists elsewhere:
  • UK: 1,100 jobs
  • Germany: 900 jobs
  • France: 718 jobs
  • Philippines: 599 jobs  — You Read That Right! More than India.
  • India: 500 jobs
Glassdoor search for “Data Scientist” finds about 26,000 jobs in USA (same results if quotes are removed).
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Question 2: How Many “Data Scientists” are There, Both in Name and in Function?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The near-term future for Data Scientists looks bright.

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

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

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

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

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

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

SO what does that mean for you?

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

And it’s not easy.

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

Here is how I would start.

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Make sure you have people who can do these functions.

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

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

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Yeah I know. It is a lot!

So, what now?

Connect with DMAIPH and we will get you started!

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DMAIPH – Decision-making, Analytics & Intelligence Philppines

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

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

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

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

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

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.

https://www.facebook.com/pg/dmaiph/photos/?tab=album&album_id=1316439141834859

 

 

NOW HIRING! DMAIPH is looking for office staff/OJT for our Ortigas office

DMAIPH is looking for office staff/OJT for our Ortigas office.

We are looking for candidates who are able to handle a variety of office roles, provide marketing and training support, assist with HR and Operations functions and/or asset with Finance and Accounting functions.

Preferably currently enrolled in or graduates of Business Management, Business Administration, Accountancy, Business Economics, Management Engineering, Hotel, Restaurant and Institutional Management, Mathematics, and Management Information Systems are likely candidates.

Requirements include:

  • Analytical mind, problem solving, well organized and can be trusted to pay attention to detail.
  • Good communication skills, ability to effectively communicate with senior management.
  • Conversational English spoken and written.
  • At least beginning skill level with MS Excel.

DMAIPH is the leading analytics training and consulting company in the Philippines.

Duties May Include:

  • Assisting with Payroll and making Payments
  • Delivering documents to government entities and notary/legal offices
  • Assisting with processing and filing HR paperwork
  • Attend job fairs. conferences and special events to represent DMAIPH
  • Assisting with office operations including coordinating with building management
  • Conduct social media marketing campaigns as directed by the Marketing Manager
  • Assisting with finance and accounting functions as needed by Finance Manager
  • Provide basic reporting using MS Excel

To find out more about this paid internship and training program, please checkout our blog http://www.dmaiph.com or our training partner page http://www.sonicanalytics.com

Include your resume and put DMAIPH Intern/Trainee in the subject line.

Job Types: Internship, New-Grad

Job Type: Full-time

 

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Apply via indeed.com

 

https://www.indeed.com.ph/viewjob?t=office+staff+ojt&jk=6f15c7896bf366d3&_ga=2.32287163.422507143.1535732709-1274046262.1535404486

Or please send your updated resume to meyerdan@dmaiph.com for consideration.

Application Questions

You are requested to answer the following questions in your submission:
  • How many years of Office Administration experience do you have?
  • What is the highest level of education you have completed?
  • Are you in Pasig?
  • Do you speak English?

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).