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Driven By Data

What’s their secret? Exploring Victoria’s Secret Dataset (Part 2)

Posted by Data Society on Apr 1, 2019 5:14:52 PM

Last week, we dove into the Victoria’s Secret dataset and discovered that they had a huge variety of not only bra types, but also colors, sizes, and materials. Whenever you start working with a new dataset, always remember to explore it first so you have a good idea of the distribution of the data and you may even have new questions. Now that we have a better understanding of Victoria’s Secret’s inventory, we can ask more questions about their pricing strategies, such as:

  • What’s the price distribution for each product category?
  • Which cup size is cheaper? And which cup size is the most expensive?
  • If you want to save money, which color is cheaper? 
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Topics: data visualization, data training, data communication, data strategy, data-driven decision-making

What’s the Secret? Exploring Victoria’s Secret Dataset (Part 1)

Posted by Data Society on Mar 20, 2019 6:13:54 PM

 Victoria’s Secret is one of the best-known brands for lingerie, pajamas, and bathing suits. Thanks to Kaggle, we have the opportunity to dive into their best-selling products and see how their pricing reflects their inventory. In this first part of our series, we’ll explore their inventory and unique products to get a better understanding of the overall dataset. This is always a best practice when you work with your own data - when you invest the time up front to get an overview of your dataset, you’ll better hone your analysis and save a lot of time in the long run.

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Topics: data science, data visualization, data training, data communication

4 questions you should ask before visualizing your data

Posted by Merav Yuravlivker on Dec 23, 2015 2:57:00 PM
Hmm, something looks fishy here. These numbers aren’t adding up!

A picture is worth a thousand words — at least, that’s how the old saying goes. But how many numbers is a picture worth? Perhaps that’s a more interesting question given the amount of charts and graphs created every day. We need to distill all the data available to us through charts and visualizations to convey a clear message. It’s the message the inspires action to change the world — or your organization.

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Topics: data science, data visualization, data training

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