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Data Management
David Loshin 0
Pushing event analytics to the edge

In my last post, we examined the growing importance of event stream processing to predictive and prescriptive analytics. In the example we discussed, we looked at how all the event streams from point-of-sale systems from multiple retail locations are absorbed at a centralized point for analysis. Yet the beneficiaries of those

Andreas Becks 0
Big Data Strategie erfolgreich entwickeln

Das Big Data Lab von SAS - Big Data Strategie 1995 - World Wide Web. Erinnern Sie sich, wie komplex und kompliziert es für ein Unternehmen war, eine eigene Website aufzubauen, Anwendungen zu definieren, diese redaktionell zu betreuen und die nötige Infrastruktur zu betreiben – heute unvorstellbar! Und sogar das Surfen

Charlie Chase 0
Stop cleansing your historical shipment data!

The real reason companies cleanse the historical demand is that traditional forecasting solutions were unable to predict sales promotions or correct the data automatically for shortages, or outliers. To address the short comings of traditional technology, companies embedded a cleansing process of adjusting the demand history for shortages, outliers, and

Cindy Puryear 0
Macro Myth: The closest non-empty symbol table

This SAS tip is from Robert Virgile and his book “SAS Macro Language Magic: Discovering Advanced Techniques”. We hope you find this tip useful. You can also read an excerpt from Virgile’s book. When CALL SYMPUT creates a new macro variable, it places that variable in “the closest non-empty symbol

Rick Wicklin 0
Direct me to the nuclear Bessels!

When I was an undergraduate physic major, my favorite professor would start each class with a joke or pun. One day he began class with a paraphrase of a famous quote from the movie Star Trek 4: The Voyage Home (the one with the whales). "Today," my professor said, imitating

Tony Adkins 0
Costing in a shared services environment

We often hear questions like: Are the shared service chargebacks to my business units’ cost centers accurate and transparent?  Will I save any money by using a centralized shared service? Why should I consider a centralized shared service? These are all good questions.  To answer them, you need to understand

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