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Scoop.it!
An agile approach to overhauling data architecture improves speed, flexibility, and innovation.
Farid Mheir's insight:
WHY IT MATTERS: I agree with those 6 recommendations. 
Scoop.it!
Data cleaning is a massive part of data pre-processing and model building for machine learning algorithms so it's something you can never miss.
Farid Mheir's insight:
WHY IT MATTERS: data is essential for AI but also all kinds of business intelligence and analytics in the "traditional" world of eCommerce for example. The post brings up some of the elements to consider when planning to cleanse data. Not a trivial task to perform automatically.
Scoop.it!
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IN THIS GUIDE YOU’LL LEARN
Farid Mheir's insight:
WHY IT MATTERS: read this short paper to convince yourself you need to go way beyond dashboards to understand the customer behaviours.
Scoop.it!
Instacart is excited to announce our first public dataset release, “The Instacart Online Grocery Shopping Dataset 2017”. This anonymized dataset contains a sample of over 3 million grocery orders from more than 200,000 Instacart users. For each user, we provide between 4 and 100 of their orders, with the sequence of products purchased in each order. We also provide the week and hour of day the order was placed, and a relative measure of time between orders.
Farid Mheir's insight:
WHY THIS IS IMPORTANT In today's eCommerce world, winners do not limit themselves to building great catalogs and payment processing experience. They actively analyze data to understand customer behaviour, to provide them with exceptional information to speed-up their shopping experience, but also maybe make them buy more or more expensive products. This is a great example of such a data analysis by grocery shopping leader instacart. It provides amazing insights into grocery shopping but also has open sourced the data for others to benefit.
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Curated by Farid Mheir
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