SAS Voices

Data Management

Blend, cleanse and prepare data for analytics, reporting, or data modernization efforts.

David PopeNovember 1, 2018 0

Why SAS?

I've worked at SAS for over 27 years and have often been asked: What does SAS do? or Why should I choose SAS? It all boils down to one question: Why SAS? While there are many approaches to answering this question, I recently came up with three short, yet powerful,

English

Artificial Intelligence | Data Management | Machine Learning

Roger ThomasMay 7, 2018 0

Magic vs monetization: AI tips for manufacturing executives

Remember the military computer Joshua from the 1983 Matthew Broderick movie WarGames? Joshua learned how to “play a game” by competing against other computers, got confused about reality, and nearly started WWIII. As depicted in that movie, Joshua isn’t all that different from Google’s DeepMind, which became a superhuman chess

English

Manufacturing

Analytics | Data Management

Jay PaulsonFebruary 12, 2018 2

Why is it important to add a human touch to big data?

In the hype and excitement surrounding artificial intelligence and big data, most of us miss out on critical aspects related to collection, processing, handling and analyzing data. It's important for data science practitioners to understand these critical aspects and add a human touch to big data. What are these aspects?

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Advanced Analytics | Analytics | Artificial Intelligence | Data Management | Machine Learning

Charlie ChaseJanuary 17, 2018 2

Why do we rely on judgment when analytics outperforms it?

Wherever there is uncertainty there has got to be judgment, and wherever there is judgment there is an opportunity for human fallibility. Donald Redelmeirer, physician-researcher Recently, I read a fascinating book titled The Undoing Project: A Friendship That Changed Our Mind by Michael Lewis (W.W. Norton & Company, 2017). Lewis

English

Manufacturing | Retail

Data Management | Internet of Things | Machine Learning

Helmut PlinkeJanuary 4, 2018 0

Data management predictions for 2018

What will 2018 unveil for the data management market? I searched expert opinions on technology trends for 2018 and matched them against my own to uncover the five major trends that I think we’ll see in data management this year: 1. Data movement becomes more important. Cloud providers have proven

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Analytics | Data Management

Helmut PlinkeDecember 7, 2017 0

Are you ready for the Chief Data Officer challenge?

The primary obstacle to becoming a data-driven business is that data is not readily available, leaving valuable insights unused in data silos. To overcome this hurdle, today’s companies are creating a new role: Chief Data Officers (CDO). Responsible for unlocking insights hidden in data silos, the CDO is tasked with

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Analytics | Data Management | Fraud & Security Intelligence

David KennedyDecember 5, 2017 1

How law enforcement can use analytics to combat the opioid epidemic

A steady drumbeat of news coverage makes one thing clear: Opioid abuse is rising and has reached epidemic levels throughout our country. Overdoses from the diversion and abuse of prescription opioids are one cause of the surge in deaths. Overdoses from heroin and other illicit synthetic opioids (such as heroin,

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Government

Customer Intelligence | Data Management

Lonnie MillerOctober 11, 2017 0

Two memorable multi-channel customer experiences

I’ve been making note of recent interactions and observations with different companies that I’ve done business with lately. My goal is to share with you real ways in which excellent customer experiences are shaped. Observation #1: Witty conversations rule As I write this, I’m sitting at a Panera Bread restaurant

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Advanced Analytics | Analytics | Data Management | Machine Learning

Charlie ChaseAugust 16, 2017 4

At the end of the day, it’s all about analytics-driven forecasting

Analytics-driven forecasting means more than measuring trend and seasonality. It includes all categories of methods (e.g. exponential smoothing, dynamic regression, ARIMA, ARIMA(X), unobserved component models, and more), including artificial intelligence, but not necessarily deep learning algorithms. That said, deep learning algorithms like neural networks can also be used for demand forecasting,

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Manufacturing | Retail

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