Resource Center
Insights to grow your business
Part One – Making Sense of Data: Auditing, Discovery, and Acquisition
Do you have enough data to get the insights you need? And if not, how can you fill the gaps? In part one of this series, we dive deep into auditing, discovery, and acquisition.
The Essential Guide to Feature Selection
Feature selection is a key step in building powerful and interpretable machine learning models, but it’s also one of the easiest to get wrong.
Making Alternative Credit Scores the Norm: How to Create a New Scoring Model
The current credit scoring model is outdated and in need of an upgrade. Read how to go about building a smarter, more accurate credit scoring model – and the data you need to do so.
Rethinking Data Acquisition With Explorium
Explore our resource Rethinking Data Acquisition with Explorium. Without the right technology – and the right data – many analytics and ML projects never get off the ground.
How to Deploy and Future-Proof Your Models: From Theory to Production
It’s no secret that while most organizations understand the importance of machine learning, most initiatives never make it off the ground. Follow this guide to guarantee you make it to production.
Start Small and Scale Smart: Do You Need a Data Science Team, Platform, or Service?
There’s no one way to start using data science. This guide walks you through the pros and cons of each approach and discusses how to allocate your budget efficiently.
AI is Making BI Obsolete, and Machine Learning is Leading the Way
Why are we still hung up on BI? It’s time to embrace a paradigm that empowers us to make smarter, better predictions using real data with machine learning.
Feature Generation: The Next Frontier of Data Science
It’s time to take feature generation – a subset of feature engineering – from an art to a science by opening up additional data sources to achieve breakthroughs in predictive models.
The Complete Guide For Data Acquisition
This complete guide breaks down data acquisition into six steps, including data provider due diligence and data provider tests to uplift your model’s accuracy.
Building the Dream Team: Who Should Be Part of Your Data Science Organization?
Creating a data science team is about so much more than tracking down the right job titles or developing the right algorithms. Find out the key roles you need to build a rock star data science team.
How Can You Enhance Your Risk Models? Finding Better Signals to Feed Them
In this in-depth guide, we reveal the real reasons your machine learning risk models are falling short, what you can do to fix them — and exactly how to tackle the problem.
Where’s the Weakest Link? Understanding Risk in Supply Networks
In our interconnected, globalized world, it’s harder and harder to track the weak spots in your supply chain. That’s why we created this handy guide to understanding and mitigating supply chain risk.
Solution Insight: Find The Right External Data With Explorium
This Solution Insight dives into Explorium’s Data Enrichment Catalog and how accessing external data through our platform works.
Solution Insight: Augmented Data Discovery by Explorium
This solution insight gives you a complete overview of augmented data discovery using the Explorium data science platform.
Security and Compliance in External Data Acquisition
Explorium recognizes the importance of security and complies with comprehensive, industry-leading standards, regulations, and frameworks.
Solution Insight: How Explorium Fits Into The Data Workflow
Learn how Explorium fits into every part of the data workflow for machine learning for streamlined data discovery and enrichment.
Explorium Solution Deep Dive
This technical deep-dive breaks down the entire Explorium data science platform.
Melio Payments Case Study
Explorium Case Study – Melio is on a mission to keep small businesses in business by providing a smart, simple B2B payments solution tailor-made for their needs.