KYC series – basic analysis

First question Contoso wanted to know is are we making money? Is that a surprise to you? Hopefully not. But we haven’t answered it yet! Primarily because though we have a strong handle on their sales side of things, but the cost data cannot be trusted. There is more business process work to do here…

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KYC – Basic description of example company

Ok, a lot about setting the stage; let’s do it. First a little bit about our example company. Here it is. Contoso Groceries UK, about $500m business. They procure and then distribute various grocery items to other smaller businesses who could be smaller groceries themselves or restaurants of various types or event caterers or even public institutions…

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Know your customer (KYC) – introduction to series

How do you make sense of sales data generated by transactions with 100,000 customers, 10000 products from 15 different sites through 10 different channels? It’s easy, you say, because there are now so many tools available to do this and this is not even big data. But it’s also hard because you don’t need big data…

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KYC series – customer lifecycle approach

There are many ways to analyze customer data. We present here the approach that may be taken with the tools that are available with Cortana Intelligence. Do some basic business analysis – get to know the customer, get to know the data, do some simple charts to see how revenue changes, margins change, what products…

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A Pricing Engine for Everyone built with AzureML and Python

This post describes the Microsoft Pricing Engine (MPE), a cloud tool for pricing optimization. MPE is easy to integrate into the business process as it uses the business’ transactional history and does not require A/B testing infrastructure to be set up. A double-residual modeling approach in MPE is the newest advanced causal inference approach to…

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“AutoML” Parameter Search for Hierarchical Demand Forecasting Optimization

In general, machine learning approaches expose many options that affect performance and accuracy. “AutoML” (Automated ML) concerns problems of optimizing over such options. Forecasting demand of products that form a hierarchy raises this kind of challenge. We recently wrote a blog post about demand forecasting for hierarchical data. We listed several approaches to reconciling forecasts…

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Announcing free online Cortana Intelligence virtual workshop on Tuesday, 6 Dec 2016

Get hands-on with Cortana Intelligence Suite If you’d like to learn how to architect solutions in Cortana Intelligence Suite and how to build intelligence into your applications, join Microsoft Architects Jin Cho and Todd Kitta for a step-by-step look at the platform. On December 6, 2016, in the “Cortana Intelligence Suite End to End” event,…

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Announcing availability of machine learning based Recommendation API inside Dynamics 365 for Operations

We now have the recommendations API integrated and available from within Dynamics 365 for Operations. In the Nov. 1, 2016 update to Dynamics 365 for operations, now you can view the product recommendations inside cloud POS. This is the first time that we bring insights derived from Cortana intelligence suite components using machine learning right within…

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Introducing Microsoft Data Science Virtual Machine

Microsoft Data Science Virtual Machine (DSVM) is a custom virtual machine on Microsoft’s Azure cloud build specifically for doing data science. It’s a powerful data science development sandbox equipped with the most popular tools for data exploration and modelling. You can provision a DSVM with a few clicks on Microsoft Azure website, and within 10-20…

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