Nasdaq launched the Analytics Hub (also called the Hub) last year as part of its mission to make markets more transparent and accessible for all by using alternative data to provide actionable intelligence on investment decisions.
Bill Dague has recently been appointed as Global Information Service's Head of Alternative Data and will oversee the expansion of "the Hub." We caught up with Bill to get a better understanding of Analytics Hub and find out exactly what constitutes alternative data.
What is your new position at Nasdaq?
I've been promoted to the Head of Alternative Data at Nasdaq. I'm responsible for leading our Analytics Hub product.
What is the Nasdaq Analytics Hub?
The Analytics Hub is our platform for alternative data . We provide our customers access to a variety of content from our partners. We add value by structuring, cleaning, and normalizing the data we host; doing things like adding global asset identifiers and standardizing timestamps. Then we take that normalized content and help make it actionable by applying Machine Intelligence to generate signals or help put it into context so that any investor or financial decision maker can use that to their advantage.
What is alternative data?
Broadly speaking, alternative (alt) data is any content that isn't typically considered in trading or investing. I like to say that alt data is "unstructured" from a financial services perspective, but it helps give a better picture of a company's financial performance. As you could probably imagine, it's pretty difficult to consistently pull value out of such a broad variety of content. That's where the Analytics Hub comes in.
What are some of the more in-demand data sets that fall under the alternative data category?
There are some staples in alternative data such as: social media sentiment , credit card transactions history, satellite imagery, and cellphone geo-location data. We've also seen a really strong interest in data created from applying Natural Language Processing (NLP), the way computers understand human language, to company filings and earnings calls .
What would you say is the most common misconception about alternative data?
I would say that many people starting out in alt data seriously underestimate the challenge of extracting value from a dataset . We are seeing a lot of firms that have gone through a period of disillusionment with alternative data over the past couple of years. There is clearly a lot of benefit to those who can do it, but it's hard. That's where we are focusing with the Analytics Hub - helping firms realize more of the benefits, more quickly.
What do you say to people who think Artificial Intelligence (AI) brings us one step closer to the fictional Skynet and a dystopian future ruled by machines?
I'd say that while we are a long way away from any kind of generalized AI like Skynet, there is a lot of benefit to be gained for society by leveraging AI responsibly. It's worth the effort to do it right.
How did you become interested in alternative data?
Alternative data is a really interesting domain because it sits at the intersection of Machine Intelligence and Finance - both of which have been passions of mine for a while. It exposes you to a lot of different problems not just in investing but also in other very specific areas that you'd probably never hear about, like global shipping communication standards (AIS) and maritime regulations.
If you weren't exploring alternative data, what would you be doing?
Machine learning on traditional data! We have a lot of great data at Nasdaq and we are just starting to explore all the potential uses for it. We sit at the center of global capital markets - there's no end to the interesting things we can learn. If I wasn't focused on bringing value to our customers through the Hub, I'd be finding ways to apply our tech and data to do it elsewhere at Nasdaq.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.