Analytics | Data Visualization | Learn SAS | Programming Tips
Sanjay Matange 0
Getting started with SGPLOT - Part 8 - Horizontal HighLow Plot

On a recent visit to an In-House Users Group meeting at a Pharmaceutical company, I presented a 1/2 day seminar on creating Clinical Graphs using SG Procedures.  Polling the audience for their experience with these procedures indicated that many SAS users are not familiar with these new ways to create graphs. So,

Advanced Analytics | Machine Learning
Charlie Chase 0
Is demand sensing and shaping a key component of your company’s digital supply chain transformation?

Depending on who you speak with you will get varying definitions and opinions regarding demand sensing and shaping from sensing short-range replenishment based on sales orders to manual blending of point-of-sales (POS) data and shipments.        Most companies think that they are sensing demand when in fact they are

Data Management
Rainer Sternecker 0
Bei DS-GVO „Auf-Sicht“-Fahren? Besser nicht!

Die EU-Datenschutz-Grundverordnung kommt näher – ausweichen oder draufhalten? In den letzten Wochen hatte ich die tolle Gelegenheit mit zahlreichen Kunden und Partnern über die neue EU-Datenschutz-Grundverordnung (DS-GVO) zu sprechen. Die Meinungen und Erwartungen sind dabei wirklich außerordentlich breit gefächert. Das ist nicht weiter verwunderlich, denn das Thema hat zuletzt stark an

Advanced Analytics | Customer Intelligence | Machine Learning
Maarten Oosten 0
Bots, collusion and accountability in pricing

In the recent article, “Price-bots can collude against consumers,” the Economist discusses the consumer effects of prices set by price-bots. The article starts with an example of gasoline pricing strategies on Martha’s Vineyard. With a small number of gas stations on the island, the price-bots can cover all competitor prices frequently

Advanced Analytics | Analytics | Data Management | Machine Learning
Charlie Chase 0
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,

Analytics | Artificial Intelligence | Customer Intelligence
David Cosgrave 0
Real-time customer experience: Accessing the whole picture

Real-time customer experience is a vital driver of growth. Acting in real-time, armed with the most up-to-date information about your customer, can hugely improve customer experience. Many of SAS’s customers have generated significant competitive advantage from trying to align closer with the real-life experiences of their customers. But how many

Analytics | Customer Intelligence
Sandra Hernandez 0
Así es el profesional de Marketing de hoy

En el lenguaje de marketing, mucho hablamos de implementar estrategias digitales omnichannel y gestionar la experiencia de cliente de extremo a extremo. Si bien hay bastantes soluciones (mapas de viaje del cliente, diagramas de ciclo de vida) y tecnologías (motores de optimización, procesamiento de secuencias de eventos y automatización de marketing)

Sandra Hernandez 0
Experimente las nuevas posibilidades: Precisión al ver con claridad

Ya no se trata de imaginar cosas. Cada día las empresas enfrentan miles de desafíos. Desde decisiones de negocio hasta procesos operativos, pasando por la manera de relacionarse con sus clientes o de preparar los informes de cumplimientos regulatorios o cuidarse de los ataques o fraudes. No son escenarios que

Data Visualization
Sanjay Matange 0
Category highlighting

When presenting information in form of a graph we show the data and let the reader draw the inferences.  However, often one may want to draw the attention of the reader towards some aspect of the graph or data.  For one such case, a user asked how to highlight one

Advanced Analytics | Analytics | Machine Learning
Charlie Chase 0
Straight talk about forecasting and machine learning

Are you caught up in the machine learning forecasting frenzy? Is it reality or more hype?  There's been a lot of hype about using machine learning for forecasting. And rightfully so, given the advancements in data collection, storage, and processing along with technology improvements, such as super computers and more powerful

Advanced Analytics | Analytics | Customer Intelligence | Data Management | Internet of Things
Andreas Gödde 0
Die Uhr tickt – Zeit für einen Umsetzungsplan zur EU-Datenschutz Compliance

In nahezu einem Jahr findet die neue EU-Datenschutz-Grundverordnung (DSGVO) Anwendung. Wer bisher dachte, das hat noch Zeit und wird nicht so heiß gegessen, wie es gekocht wird, der wurde von der Ankündigung des Bayerischen Landesamts für Datenschutzaufsicht überrascht: Bayern kündigt schon erste Kontrollbesuche an. „Abwarten und nichts tun ist mehr

Advanced Analytics | Machine Learning
Dariusz Jańczuk 0
Is intelligent content on the web the answer to mass content blocking?

As the internet grew in popularity, the marketing industry was quick to see that it had become an important channel for reaching out to potential customers. Websites increasingly began to host ads that were often unconnected with the site content. Advertising content became more widespread and unfortunately, also often obtrusive.

Advanced Analytics | Analytics | Customer Intelligence
Scott Nalick 0
When everything is analytics, nothing is analytics...?

The widespread adoption of the term "analytics" reminds me of the evolution of the term "supply chain management." Initially the term focused on supply chain planning. It involved demand and supply balancing and the heuristics and optimization tools that came out of advanced planning and scheduling. Over time practically everything was included

Advanced Analytics | Analytics | Data Management | Internet of Things
Andreas Becks 0
Analytics für IoT - So wird Vision zur Realität

Kennen Sie Kevin Ashton? Der britische Technologie-Pionier hat am Massachusetts Institute of Technology (MIT) einen internationalen Standard für RFID mitbegründet. Was aber vielleicht noch wichtiger ist: Vor fast 20 Jahren hatte er eine Vision von Computern, die Informationen über Gegenstände des Alltags und der Fabrikation sammeln und mit diesen Daten

Andrew Fowkes 0
In stock we trust

Success in the retail space boils down to one simple function: the conversion of sales. However, retailers can only do this if they have stock readily available. Missing a sales opportunity due to poor stock management just won’t cut it in today’s marketplace. How can we resolve this basic problem

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