Explorium's Data Insights Blog
Where data, marketing, and sales professionals come together
Could ML-Powered Risk Models Really Spot OZARK’s Schemes?
It takes Marty Byrde less than three episodes of television to go from white-collar embezzler at a major bank to blue-collar money launderer for the Mexican drug cartels. And boy, does he make it look easy. The money laundering schemes at the heart of Netflix’s hit show OZARK are slick and surprisingly low-tech. While today’s […]
Domain Knowledge in Data Science: Are Your Models Ready for Business?
Data science for business is a very different beast than building models in an academic or purely scientific context. You aren’t looking for patterns simply because they’re food for thought, inspire further questions, or demonstrate interesting dynamics and behaviors. You’re looking for patterns because someone in your company wants to know what action they should […]
How Will Data Privacy Look in The Future?
Never in history have so many government bodies around the world had so much scope, opportunity, and — most importantly — public support to harvest intricate, personal data on their citizens. The global COVID-19 pandemic has seen emergency surveillance measures that would make Orwell gasp, introduced with little resistance even in the most privacy-conscious nations. […]
How To Communicate Your Marketing Questions for Data Scientists
When you make accurate predictions, you make smarter business decisions. This is the core value data science offers to marketers. It’s easy to get caught up in the buzzwords, but AI marketing automation and machine learning tools will only help you if a) you know exactly what you’re looking for, and b) you can communicate […]
Reframing the Connection Between Data Science and Automation
AI has become a buzzword, even as machine learning (ML) and data science push toward automation. We’ve all seen a million articles about how AI will revolutionize this or that, from agriculture to video games. The hype is enough to make anyone skeptical. But in terms of real impact, few areas have really maximized the […]
What Happens When The Definition of Risk Changes?
Risk and probability are based on data. You establish the statistical risk of losing an investment based on other investments that didn’t work out. You assess whether someone is likely to repay a loan based on their credit score and other reliability indicators. But what happens when you want to calculate risk for an incident […]
Asking the Right Questions: How Machine Learning Improves Your Insights
A good data scientist is a bit like a good journalist: they know how to ask questions so precise and to the point that there can be no vague, misleading answer. Data science is all about asking these sharp, specific questions of your data — and the techniques involved in machine learning guides you to […]
How to Navigate the New Data Science and Machine Learning Landscape
We’re living through unprecedented times. Until this moment, organizations were successfully using data science models, machine learning, and other types of AI across the funnel to gain visibility throughout their business and sharpen their competitive edge. Suddenly, many of these organizations find themselves stumped. Without warning, the data — and in many cases the models […]
The Three Skills You Need to Instill in Your Data Science Team
Data science and AI have enormous potential to make your organization run more efficiently and profitably. They can be used to optimize processes, identify emerging risk and fraud attempts, spot emerging commercial opportunities, and serve your customers better. You know that. Your team knows that. But does the rest of your organization know? Top data […]
How Dynamic Risk Modeling Gives Your Detection a Boost
It’s not an overstatement to say that detecting risk is a tough task, even with the best technology available. The changing face of fraud, supplier risks, cyber crimes, and a host of other factors risk leaders need to track means that the approach to detecting them must be equally multi-faceted. However, we seem to be […]
Why You Need Data Catalogs, Not Databases
Congratulations! You’ve embraced machine learning and data science and your organization is well on its way to building a system that helps you deploy predictive analytics for greater insights. You’ve already done a lot of the heavy lifting, from finding the right platforms and tools to help you build your models to understanding the steps […]
Where’s the ROI? Demonstrating the Value of Data
In today’s business world, data means a lot of things to a lot of people. It’s a means to an end, a treasure trove of insights, and even the currency of the future. What’s not always clear, at least to non-technical stakeholders in an organization, is why they should care about it. It’s something great […]
B2B Marketing Fit Data
What is B2B Marketing Fit data? B2B marketing fit data is a set of static data that helps organizations define if a contact or lead is a good fit in its total addressable market. It consists of demographic data of a contact such as job function, level, skills, and responsibilities. It also contains technographic data […]
Employment Data
What is employment data? Employment Data typically includes labor force statistics and employee information such as name, employer, position, address, number of hours, salary or payroll information, employment rates, and status. It also covers economic data, demographics, interview difficulty, benefits, interviews, number of published salaries, number of published job openings, and number of employees by […]
Could Walter White and Marty Byrde Fool The Best Risk Models?
Crime doesn’t pay — any TV cop will tell you that much. But, what about their counterparts — those slick TV criminals that, season after season, manage to elude the law with clever schemes, quicker wits, and just plain dumb luck? What about Walter White, the science teacher turned meth-making mastermind in Breaking Bad, who […]
Why Data Marketplaces Are the Future of the Data Economy
As you know, every second of every day, we’re generating and acquiring new data. As you read this, someone is collecting data on the fact that you are reading it. Someone is collecting data on your device type, your browsing habits, where you fit within a larger pattern. They’re predicting your interests, values, maybe even […]
Want to Get People Excited About Your Machine Learning Project? Tell Them a Story
In 2007, two roommates struggling to make rent in San Francisco had a bright idea. A major design conference was coming up and hotel prices were soaring. What if, the roommates thought, they rented out air mattresses on the floor of their apartment to cash-strapped attendees — a kind of designers’ (air)bed & breakfast? It […]
How to Connect to the Data Ecosystem
Pinpointing the most useful machine learning data and figuring out how to combine sources to create accurate, meaningful models is one of the most business-critical areas of data science. Increasingly, data scientists are realizing that the data they have in-house might not be extensive or complete enough to do that on their own. That solely […]