Viva Las Vegas: Data and the Consumer Electronics Show

This week I will be heading off to the Consumer Electronics Show in Las Vegas. Suffice it to say, I am excited about the trip: as someone who has only ever seen CES on television, I am really looking forward to hearing some of the talks and walking the show floor.

 The path to the CES has been an interesting one for me: prior to joining 1010data as its Chief Evangelist this past November, I was a Director of Strategy in the Central Intelligence Agency’s Directorate of Analysis. For the past five years, I worked towards answering the question, “How might we bring the benefits of data science to all users, regardless of their technical acumen?” That was the question that brought me into contact with 1010data, first as part of a (skeptical) audience and then as a customer. 

Since I started working with 1010data as a customer, I joke that they “broke” me: thinking about data in the context of a massive, high-performance “spreadsheet” is now my default setting . . . and I have come to see that even small amounts of custom structured data can produce some remarkable analytic insights. 

When I look at CES’s schedule, I am excited at the prospect of learning about the state of the debate around looming technological innovations and the data these innovations might generate. In this, Cade Metz’s article in Wired (“Google Open-Sourcing TensorFlow Shows AI’s Future Is Data”) has stuck with me; while the article focused on data, and proprietary data at that, the underlying notion that a single data set (or stream) is rarely wholly satisfactory resonates. 

Given the rise of wearables, and the looming prospect of the Internet of Things, we are looking at a sensor- (and data-) rich world. The data generated by these technologies is likely to be incredibly interesting. That said, no single data set is as powerful as compilations of different types of data drawn from different sources. 

This is the exciting thing about 1010data analytic platform: it is a massive analytic fabric that simplifies joining disparate data sets together. Once the data is joined together, you can quickly do some amazing (read: deep or complex) analyses. As I will discuss at the National Retail Federation’s Big Show 2016 later this month: the combination of scale, flexibility, and speed dramatically lowers “the cost of curiosity.” 

With the right data protection policies and practices, the possibility that disparate data streams generated by consumer devices might be joined together in ways that make our lives better is exciting. 

If you are interested in my takeaways from the talks that I attend, or would just like to say hello, please follow me on Twitter: my handle is @StratGleeson. 

If you are unfamiliar with 1010data, we encourage you to watch a short video that we put together to explain what we might be able to do for you and your company: “An Analyst’s Tale.