Paying it Forward – You Can Help

As a data science manager, you know how important talent is to our work.

The purpose of this group founded by Shivanku Misra of PayPal is described on the Career in Analytic’s LinkedIn site:

Analytics and data science have been receiving well deserved attention in the recent times, hence generating great amount of interest in this career domain.

This leads to a growing need of enabling the right guidance that not only helps new analytics employees get the best start, but also lets the data science leaders get connected to new talent that they could potentially hire.

-Career in Analytics Purpose Statement

Navigate to the site and join the group. I have had the pleasure of talking with Shivanku, and his initiative is a thoughtful approach to growing the underlying asset base of our industry – your people.

The CiA site started a new, online interview series today that features analytics professionals. The intent is to begin a conversation among community members whether you are a practitioner or a recipient of data.

CiA_image

I was quite honored to have the opportunity to sit down with Shivanku and give the first interview. There will be questions and answers during the week and then another professional will be featured.

See you at the CiA site.

Enterprise Analytics: How to Manage a New Challenge

graphic of internet of Things - today
Read More about what inspired this graphic at http://techcrunch.com/2016/03/29/whats-trending-in-the-iot-space

Today I had the opportunity to talk to NDU’s graduate students in the Analytics and Simulation for Enterprise Architecture course. We discussed the topic of Enterprise Analytics and Data Science Teams. Key points included the Internet of Things and Data Lakes to bring data and science together.

I appreciate the interest in this growing topic and there were some good questions at the end. Dr. Mark McGibbon had the foresight to include this topic in the syllabus. I look forward to comments on this post. Here is a summary of the discussion points:

QMA

Models are only good to the extent that they provide actionable Answers to the Questions that leaders have.     -Jay Gendron

  • For starters…it all starts with a good question. Give a data scientist a pile of data and they will find something. Will we provide you with something relevant to your business?
  • Set the foundations. Big Data (or is it now Fast Data and Different Data?) as well as Analytics
  • Data Science is a team sport. Fortunately, it looks like the field will avoid the equivalent of a “webmaster”…analytics is a team sport
  • Presented my framework linking IoT-Professionals-Data Lakes. It is a relational thing…up, down and all around
  • Internet of Things (IoT). This was a big point of today’s talk
      • First, I presented a context based on a just released, market analysis report on the IoT
      • Then we had a little fun showing how biologic systems are the future. We enjoyed the first 3 minutes of the talk “Connected Cows?” given by Microsoft VP for Information Management and Machine Learning, Joseph Sirosh, at the Strata + Hadoop 2015 conference

The best air quality monitors we will get is when we can integrate their signal into the internet -Jay Gendron

  • Data Lakes. This is not a zero-sum game, and it is a timely and controversial topic. They have both strengths and weaknesses, but to avoid them would appear to be a great loss for data companies…and as Sirosh said in the video “All companies are data companies.”
  • After the presentation, there was interest in learning more about two practical analytic mentalities
    • Scales of measurements. Understanding the “as is” and “to be” data types in your analytics plan. This topic was solidfied until 1946 in a journal article in Science by S. S. Stevens
    • Cleaning and Exploring Data. Both of these are pre-processing steps in analytics and consume over 80 percent of the analytic schedule. Yet, these are two topics that are accessible to a larger audience
Question and Answer Session

The Q&A session was not very long, but two of the more popular questions came up:

  1. How is this applicable to our space?  A: There are many areas of applicability. It does take some good leadership and management combined with creative thinking to tease out the benefits. But, as shown in the Connected Cows? video there are many, many areas yet untapped to apply an IoT mentality. Consider the work already done with text analytics and social media to predict uprise. What could be done with streaming data on weapon performance and health (not unlike manufacturers do with machine spindle speeds today to anticipate failures…and lost production
  2. How can we afford this Big Data approach? A: How can we afford not to adapt? The technology (such as Hadoop) is already appearing in government organizations. A true cost will be to identify and secure the talent to harness the technology. Consider the ROI in the Connected Cows? video and then look at your own situation to build a business case.

I was very pleased to have the opportunity to present this topic of Enterprise Analytics. What do you think? What portion of the discussion was most most interesting? most concerning? Where do you see Enterprise Analytics going in your organization?

Jay Gendron is a data scientist, business leader, artist, and author who writes about how good questions and compelling visualization make analytics accessible to decision makers. He is an award-winning speaker who has presented internationally. His book Introduction to R for Business Intelligence will be available this summer through Packt Publishing.

Meeting the Data Science Leaders

 

NDU

I am very pleased that tomorrow I will have the opportunity to meet with students in the NDU graduate course on Analytics and Simulation for Enterprise Architecture. The discussion will kickoff at 9:00 AM. I will post an update to share what was learned during our time together. I will be presenting these slides on Enterprise Analytics.

Best,
Jay Gendron

The Future is What Happens When People Embrace Open Data

Open data is a thing, an idea, and an ideal. Open data is one of those “superhero words” alongside its cousins the Cloud and Big Data. I like to call them superhero words because they are supernatural forces that seemingly defy definition and can’t be seen. Yet they provide very tangible value to their communities.

                                                 [1,2]

Open data boasts powers like omnipresence, super-flexibility, and hyper-prescience. All this, and it’s all free!

No free lunch?

Perhaps you have heard it said, “There is no free lunch.” Open data does challenge that idea when you look across the nation and see the power in providing civic data to people with the talent to make it come alive. According to an article in govtech, guidance exists that open data should be both “technically open” and “legally open”. Translation:  open data is machine- readable and licensed to allow use without restriction [3].

Local Superheroes

We embrace Open Data this in Norfolk, Virginia with our own superhero groups like Code for Hampton Roads and the Open Data Initiative, to name just two. Both of these help form the bedrock of people who have decided to engage with civic leadership to make our home a better place.

“Once you’ve got a wide audience, you can begin to use your open data to drive citizens to actually doing things with it and implementing broad change.”

Consider this fantastic story of people answering the call. The time is 2014 and a local Brigade of Code for America holds its annual hackathon to support the community. When you live in a place close to the water, travel routes quickly become choke points – that creates a problem for transit service schedules [4].

“find places where people with technical skills can make a difference” -Kevin Curry

This group of technical experts from Code for Hampton Roads decides to help put transit data to good use by creating a mobile app that provides actual bus arrival times accurate to within a minute or two. The cost to the city of Norfolk – opening a data port. The HRT Bus Finder app is still in use today, and the Brigade maintains it as a free, volunteer effort. {Truth be told, their weekly work usually does involve the cost of a pizza or two.}

Great work citizens! Keep it up. Do you want to be a superhero?

But be careful…citizens in action are unrelenting superheroes that just keep going and going. Thank goodness.

 

Cited Works:

1. [Image of Comic] By “Tales of Suspense #39” at The Grand Comics Database. Retrieved March 4, 2005., Fair use, https://en.wikipedia.org/w/index.php?curid=1569163.

2. [Image of Iron Man] At Marvel Comics’ official website. Retrieved May 21, 2010., Fair use, https://en.wikipedia.org/w/index.php?curid=27426317.

3. Shueh, J. (2014, March 17). Open data: What is it and why should you care [Web blog]. Retrieved from http://www.govtech.com/data/Got-Data-Make-it-Open-Data-with-These-Tips.html.

4. Grimes, C. (2014, July 23). Hampton Roads transit agencies turning to apps that provide real-time bus schedule information. The Daily Press. Retrieved from http://www.dailypress.com/news/traffic/dp-nws-regional-transit-apps-20140723-story.html.

Jay Gendron is a data scientist, business leader, artist, and author who lives in Norfolk, Virginia and writes about how good questions and compelling visualization make analytics accessible to decision makers. He is an award-winning speaker who has presented internationally. He is a member of Code for Hampton Roads and is proud of the work they do contributing skills to improve civic and municipal access to data. He is the founder of the Meetup “try.Py – Learn Python”.