Any data-driven organization worth their salt today knows that it’s not just how much data you find but how relevant it is. Ten years ago, having
As they say, the proof is in the pudding, and data preparation is where the pudding is put together. Any mistakes you make here will be
Like Italian cooking, data science is all about quality ingredients. It’s not enough to simply have a lot of data; you need to make sure the
Money never sleeps, dataflows never slow, and a data leader’s job is never done. You aren’t just thinking about how to make sense of the data
With so much data in your own stores, it’s tempting to think you have all you need to start producing great predictive insights. This might be
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?
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
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
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
