Accessability Links
Cookies on our website
By continuing to use this website we will assume you are happy to receive cookies as outlined in our cookie policy
Accept Policy


Interview with Predictive Data expert Eric Siegel

Posted by: Adam Rabinovitch 21 Mar 16  | Technology

In the first of many, recruitment consultant and expert in all things data and analytics, Adam Rabinovitch, talks to thought leaders throughout a number of specialist industries. This month Adam  interviews Eric Siegel; founder of the Predictive Analytics World conference series and author of "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Eric tells us his thoughts on the future of predictive analytics, how small businesses can use it effectively, the impact on cyber security and more.


What are the biggest areas of opportunity/areas you think people should tackle in predictive analytics?

Predictive analytics is the flagship application of big data. The most valuable thing you can do with data is analytically learn from it to predict, and apply those predictions to directly inform millions of operations/decisions in marketing, financial risk, fraud detection, web conversion, etc.

Since predictive analytics' per-individual predictions directly inform the great numbers of per-individual decisions, it is by definition the most actionable win from data.

What is the curse of big data?

Overhype. "Big data" doesn't actually mean anything specific other than "a lot of data." In fact, it's a grammatically incorrect way to say that, like saying "big water" instead of "a lot of water." What's astounding about data is how quickly it is growing, not its absolute size today - and what's even more enthralling is its value in that it is predictive. 

The term "big data" tells us to get excited about doing something "smart" or valuable with data, but it doesn't specify what. The term does not allude to any particular technology, methodology, or value proposition. Fight against that by pursuing a specific, actionable use of data. One shining example is predictive analytics.

Most everything I said here also applies to the term "data science." But both terms refer to a thriving culture of creative "data wonks" and technology experts, even if they do not refer to any specific technology.

Any words of wisdom for data science students or practitioners starting out?

Getting hands-on experience with real data is critical. One way to do this is to participate in a public predictive modeling challenge such as those hosted by Kaggl.e

What impact do you think companies will have on cyber-security and hacking in a Data Science & Big Data team?

Predictive analytics is employed to detect malicious online activity just the same as it is used to detect fraud and other types of crime. In all these cases, the data encodes both positive and negative historical examples of whatever you are trying to detect and predict, and that data is leveraged, learning from it analytically in order to scientifically earmark those instances most likely to turn out to be malicious.

What are your top predictions for predictive analytics?

I recently addressed this exact question in Big Think:

  1. Consumer demand for predictive analytics will surge
  2. Predictive analytics will become a standard safeguard for business
  3. Termination of NSA bulk data collection will be reconsidered
  4. 2016 presidential candidates will use predictive analytics to appeal to voters

How can small business benefit from the use of a data scientist?

It is the size of the data and the size of the operational process you'll render more effective with analytics that matter more than the size of the organization. That's what defines the value proposition and business opportunity. For example, a small organization that sends a holiday direct mail catalog annually to 100k addresses could do very well to predictively target that marketing campaign.

Keeping an eye out for your next career move in big data or IT? Search our roles here

 

Back to Top