Quick Data Science Survey

If you are in the Philippines and work with data everyday in your job, I’d like to invite you to take my survey.

Next week I will be speaking about data science in the Philippines, specifically trying to answer the question, “Just How Many Data Scientists Are There In The Philippines Anyway?”

It’s a short 7 question survey that will help me validate some of my research.

Here’s the link:

https://www.surveymonkey.com/r/WKG9VJ5

Thanks for taking a few minutes to help address on of the biggest questions facing the Philippines today.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

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Most Impactful Ways To Becoming a Great Analyst

As a follow up to a survey I sent to several hundred of my LinkedIn connections a few months back. I sent the survey to connections working with data analytics on a regular basis.

I told them I was talking with a young professional just getting started in his analytics career. During our conversation we discussed what is most important to being a great analyst. I asked for their opinion, of the following ways to learn about analytics, which one has been the most important in your career path?

  1. Formal Education – A degree or certificate in an analytics related field.
  2. Self-Learning – Using trial and error and online resources.
  3. Subject Matter Experts – Being trained/mentored by an expert.
  4. Seminars/Workshops – Attending events to acquire new knowledge.
  5. Technical Training – Attend training on specific technical areas.
  6. Other – Please provide a brief description

 

Here are some pearls of wisdom from some of the replies I got… keep in mind these are all from well established analytics professionals:

“the most important in my career path is self-learning as most of the things we’re doing like journal reading and implementing algorithms needs less dependency with the people you are working with but requires collaboration with them and this requires you to solve problems by yourself and implement things by yourself but communicate them properly to the people you’re working with.”

If you don’t have the drive to do this, you will be an analyst in name only.

“Self-Learning – Using trial and error and online resources. World changes too fast for any of those others to matter.”

In the 15 years I have been doing analytics without any formal education in data-related fields I can say that this is 100% true. To be a great analyst you have to always been learning.

“your ability to tell the story behind all the numbers will make you an indispensable asset and an outlier in the increasingly growing population of analysts. Management almost always don’t have the time to read all the numbers in tables, spreadsheets, and reports, but they will surely appreciate instantly seeing the big picture presented in a “one-pager” report prepared by analysts. That almost always makes an analyst “great” in the eyes of the report consumers.”

Yes! If what you spend your blood, sweat and tears on does influence decisions, then you are working on the wrong place.

#2 and #3 have been important. Having a mentor to coach you side by side gives you accountability to progress in your work and learning curve. Naturally, this will push you to self-learn: trying out what you’ve learned and testing.”

Having a mentor is so important to help you get access to the actual learning experiences you need to evolve and excel as an analyst.

“spending time with the consumers of the analytics is especially important. Learning how they look at the data, and/or want to look at the data. What is important to them. What really matters. Too much non-essential information and you’ll loose them. Targeting their needs with relevance and precision will win them.”

Another big point that is often overlooked, if you are spending time producing repots and they don’t take customer insights into account, you have a big blindside.

“The most important thing to being a great analyst is to have a great sense of awareness. For me, self-learning has been the most important.”

I cannot imagine anyone being a great analyst if you didn’t have at least a bit of an ego mixed in with a Superman complex. Great analysts live to fix things.

It’s interesting to note that only 2 of the 50+ replies I got form surveying my LinkedIn connections said formal education is the most important.

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Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

 

 

Survey Results: Devote More Time For Data Analysis

Most Analysts Spend 50% of Their Time Finding Data

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

Most analysts spend most of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Most Analysts Spend 50% of Their Time Finding Data

Most analysts spend most of their time finding data.

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

In fact, most analysts I know spend 50% of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

DMAIPH Quick Data Survey

A few months back I sent a quick survey to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Here is the question I asked.

Greetings!  I’m hoping you can help me gather some data for a book I’m working on. If you had to breakdown the work you do into 3 buckets; finding data, analyzing data and reporting data, what would the % of each be? A quick reply with your breakdown would be hugely helpful in my research. Thanks!   Dan Meyer, Analytics Champion, www.dmaiph.com

I got back over 400 replies.

Here is how they broke down.

 

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

The higher the %, the more each analyst spent time doing that particular phase of analytics.

Here are some of my takeaways from this simple (and very nonscientific survey)

  • I was surprised to see 45% spend half their time or more on finding data. To me this is one of the telling signs that Big Data has led to a shortage of top analytics talent.
  • Only 1 out of 4 analysts are spending 20% of less of their time finding data. These are generally senior analysts, well established in their company.
  • Only half of my analyst connections are spending 40% of more of their time on conducting analysis. With significant time spent on finding and/or reporting data you can imagine a lot of important discoveries are being missed and opportunities lost.
  • Only 1 out of 3 analysts are getting spend my recommended 50% or more of their time actually doing analysis work.
  • Based on my survey, reporting gets shortchanged a lot. All in, 96% of respondents spend 30% of their time of less on reporting.
  • My recommendation is that you spend about 30-40% of your time on the reporting aspect, and sadly only 4% of my analytics connections are able to do that.

In an ideal world, I would expect an analyst to spend no more the 30% of their time on finding data, and at least 30% on reporting their findings, leaving more or less 40% to do the actual analysis.

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This breakdown is based on my own experience as an analyst as well as seeing how analyst working for data-driven companies work.

Only about 30% of my 400+ analytics focused LinkedIn connections come close to meeting my recommended breakdowns.

Which means I have a lot of work to do.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.