Explorium Blog

  • Top Tips for Data Preparation Using Python

    Top Tips for Data Preparation Using Python

    Your machine learning model is only as good as the data you feed into it. That makes data preparation (or cleaning, wrangling, cleansing, pre-processing, or any The post Top Tips for Data...

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  • Explorium Announces $31M in Series B Funding to Accelerate Growth

    Explorium Announces $31M in Series B Funding to Accelerate Growth

    Explorium is changing the way companies find and use data for superior machine learning models and business decisions.

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  • Could Machine Learning Help Tom Haverford Save Entertainment 720?

    Could Machine Learning Help Tom Haverford Save Entertainment 720?

    Machine learning is a key tool for improving marketing. Let's break down how Tom Haverford from Parks and Recreation could have used it to save e720.

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  • Turning Data from a Cost Center into an Asset

    Turning Data from a Cost Center into an Asset

    Many organizations see data acquisition and management as a business expense. You may hear questions like, what does it cost to collect and capture this data? The post Turning Data from a Cost...

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  • Could ML-Powered Risk Models Really Spot OZARK’s Schemes?

    Could ML-Powered Risk Models Really Spot OZARK’s Schemes?

    In some ways, OZARK’s main plot seems too good to be true, and it might actually be. In the real world where ML-powered risk models exist, could Marty Byrde really get away with his schemes?

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  • Domain Knowledge in Data Science: Are Your Models Ready for Business?

    Domain Knowledge in Data Science: Are Your Models Ready for Business?

    In this in-depth article, we explain how the right questions will help you get the domain knowledge you need for data science for business.

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  • How Will Data Privacy Look in The Future?

    How Will Data Privacy Look in The Future?

    Data privacy continues to be a major hurdle for risk officers. In this article, we explain how the global increase in data surveillance creates short term opportunities but long term risks.

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  • How To Communicate Your Marketing Questions for Data Scientists

    How To Communicate Your Marketing Questions for Data Scientists

    Marketing data science has the power to transform businesses. However, for success, marketers need to know how to communicate their goals properly.

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  • Reframing the Connection Between Data Science and Automation

    Reframing the Connection Between Data Science and Automation

    Automation and data science are a match made in heaven. It's up to data leaders to understand how to introduce it to their teams in the right way.

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  • What Happens When The Definition of Risk Changes?

    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 The post What Happens When The...

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  • Asking the Right Questions: How Machine Learning Improves Your Insights

    Asking the Right Questions: How Machine Learning Improves Your Insights

    In this article, we explain how the data science revolution is all about asking questions that get precise answers for the future.

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  • How to Navigate the New Data Science and Machine Learning Landscape

    How to Navigate the New Data Science and Machine Learning Landscape

    In this article, we explain how to turn the biggest data science challenges of the moment into business opportunities.

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  • The Three Skills You Need to Instill in Your Data Science Team

    The Three Skills You Need to Instill in Your Data Science Team

    To succeed in the data science field, you need more than just technical acumen. We reveal the secrets to making your team indispensable.

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  • How Dynamic Risk Modeling Gives Your Detection a Boost

    How Dynamic Risk Modeling Gives Your Detection a Boost

    Dynamic risk models add a dimension to rules-based risk modeling that makes you more agile to the changing world.

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  • Why You Need Data Catalogs, Not Databases

    Why You Need Data Catalogs, Not Databases

    When it comes to external data for machine learning, data catalogs provide a handful of time-saving benefits over databases. Learn more.

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  • Where’s the ROI? Demonstrating the Value of Data

    Where’s the ROI? Demonstrating the Value of Data

    Leaders must find a way to prove, tangibly, that embracing data and investing in better ways to use it has true value and real ROI.

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  • Could Walter White and Marty Byrde Fool The Best Risk Models?

    Could Walter White and Marty Byrde Fool The Best Risk Models?

    Walter White and Marty Byrde are known for their money laundering schemes. But could they really fool the best risk models banks have today? Let's look.

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  • Why Data Marketplaces Are the Future of the Data Economy

    Why Data Marketplaces Are the Future of the Data Economy

    Data marketplaces make the lives of data scientists looking for machine learning datasets much easier. Read how.

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  • Want to Get People Excited About Your Machine Learning Project? Tell Them a Story

    Want to Get People Excited About Your Machine Learning Project? Tell Them a Story

    Top tips to engage stakeholders at every stage of the data science project life cycle.

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  • How to Connect to the Data Ecosystem

    How to Connect to the Data Ecosystem

    In this article, we explain where external data comes from, the key challenges, and how to connect and utilize it with data science solutions.

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