listeningTo complement the perspectives of our recent guest bloggers, today I’m sharing three ways of listening to data scientists.

These will include a (potentially) free recommended eBook, an engaging blog post and a punchy video.

Peter, Robert & Francesco have made a case for data & AI potentially transforming businesses & sectors. As part of our month focussed on applications of data & analytics, I also want to share real life case studies. What are the real data scientists in business doing?

Fortunately, there are both some generous publishers and excellent resources available. So, in this post we will hear from 28 different data scientists and 10 companies.

So, let’s get stuck into hearing about the reality of data science & machine learning.

A (potentially) free eBook shares the voices of 25 Data Scientists

It’s encouraging to discover publishers that have such confidence in their content they let buyers choose what they pay. This is the case with a very useful new book, called “The Data Science Handbook“.

Edited by Carl Shan, Henry Wang, William Chen & Max Song, it includes an interesting mix. From stars like Jonathan Goldman & DJ Patil at LinkedIn (the latter going on to The Whitehouse), to newbies. They each reflect on their own career journeys, trends/challenges for the industry & advice for others. The style is engagingly conversational – so you get a feel for the ‘voice’ of each data scientist.

As well as the opportunity to read through the whole book, the editors suggest recommended interviews for:

This is well worth downloading or buying the paperback. If you do opt to download the ebook, you pay what you want. Their suggested donation of only $19 seems fair though. Here is the link to get your copy & sit down with 25 Data Scientists:

The Data Science Handbook

Check out The Data Science Handbook! A compilation of interviews from leading data scientists at Uber, Palantir, LinkedIn, Facebook and more!

Quick review of how 10 companies are applying Machine Learning

Perhaps it’s my British reserve, but I did initially balk at reading a post about “10 companies using Machine Learning in Cool Ways“. But this post from the Business 2 Community is actually insightful & relevant.

In this brief canter through the 10 companies, Dan Shewan brings to life their diversity. It’s a good example of a more visual and shorter blog post that prompts your own thinking.

Some examples are more familiar, like Google & the Social Media giants. But I wasn’t aware of the interesting applications by Yelp, Edgecase or IBM Healthcare. Dan is right, that the artificial voice application by Baidu is disconcerting, but it’s also fascinating.

I hope you find an example that sparks an idea for your business. Why not share the post with other leaders and see if the same of different examples strike you each as relevant?

10 Companies Using Machine Learning in Cool Ways

If science-fiction movies have taught us anything, it’s that the future is a bleak and terrifying dystopia ruled by murderous sentient robots. Fortunately, only one of these things is true – but that could soon change, as the doomsayers are so fond of telling us.

Listening to what keeps 6 top Data Science leaders up at night

All that talk of innovation across 10 different companies, could make Machine Learning sound easy. But, every practicing Data Scientist will be able regale you with stories of how it isn’t. From missing data to legacy IT to ignorant stakeholders, some of their frustrations are all too familiar.

Digging deeper though, it can be insightful to ask some of those at the top of their field, what they worry about. The blogging team at DataScience.com have done just that. What they discovered is worth reading.

In this short, punchy, video, they interview 6 more Data Science leaders:

It’s encouraging to hear that it is not just the expected concerns, about data quality & attracting/retaining talent. Most of these leaders express concern about misuse of data science. Most are focussed on aiding better quality decision-making & focussed on real world impacts.

That is just the sort of holistic customer insight leadership thinking that we advocate on this blog. Hope you enjoy the video:

What Keeps Data Experts Up at Night?

DataScience.com asked experts from Google, Live Nation, Oracle, and other cutting-edge companies what data challenges keep them up at night.

Who are you talking to?

Hopefully, the content we have shared in this blog, has encouraged conversations. What I mean is, I hope you want to get out and talk to other data scientists or data science leaders.

The ebook, blog post & video shared above are intended to be an appetiser. As we enter the autumn conference season (or you have internal events), make use of these.

Real insight can come from sitting down with other Data Science leaders and just listening to what’s on their minds.