Manufacturer of vehicles and spare parts
More and more manufacturers have access to Big Data, complex and massive information collections almost impossible to process with traditional methods, but few have the infrastructure and processes to use it effectively.
This massive corporation manufactures large-scale products for retailers of large boxes, which in turn sell to individuals. The manufacturer obtains sales data from those retailers. Finding and analyzing sales trends, the popularity of the elements and other valuable ideas hidden in those data can be key to driving the bottom line.
The manufacturer received terabytes of transaction data at the weekly line item level. The company’s technology only had the ability to handle the value of a few weeks at a time.
Pi Data Strategy & Consulting showed this firm how to use Hadoop’s substantial storage capabilities and its processing power that can make Big Data analysis very simple.
We took a lot of data from the manufacturer and loaded it into Microsoft Azure HDInsight, a cloud-based Hadoop platform. Then we used Power BI to show different ways of consuming that information. The HDInsight concept eliminates the need for an expensive Hadoop cluster and many of the management requirements.
Azure HDInsigth – Power BI – Azure ML
Using the data from the point of sale and the shipping quantities of the product, we built a predictive model using Azure ML that allowed the manufacturer to predict when a location would run out of stock to proactively send more products.