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Analytics

Find out how analytics, from data mining to cognitive computing, is changing the way we do business

Analytics

SAS ColombiaOctober 27, 2016 0

¿Se imagina la analítica bajo la mirada de Elvis, MacGyver y otros famosos?

Si usted está en Bogotá este 2 de noviembre y es uno de los invitados especiales de la Segunda Convención Latinoamericana de Analítica 'Analytics Everywhere', podrá saber cómo el Rey del Rock & Roll, el recursivo personaje de la TV y muchos otros personajes le dan 'otra mirada a la

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Analytics | Data Visualization

Robert AllisonOctober 27, 2016 0

How to scare up a few good graphs for Halloween

Halloween appears to be my favorite holiday, because I seem to have more graphs related to it than any of the others. And since Halloween is just a few days away, I thought you might like an easy way to see all those graphs. Here's are links to my previous Halloween-related blog

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Analytics

Gerhard SvolbaOctober 27, 2016 0

Mehr SAS Know-How für Data Scientists

Kennen Sie diese Situation? Sie sollen dringend eine komplexe Auswertung fertig stellen. Die Daten wurden zu spät geliefert und die Qualität und Struktur der Daten waren weit vom erwarteten Standard entfernt. Der Zeitdruck der Ergebnispräsentation ist groß, und Ihr SAS Programm tut immer noch nicht genau das, was Sie als

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Advanced Analytics | Analytics

Shipments vs Consumption chart

Mike GillilandOctober 27, 2016 0

Changing the paradigm for business forecasting (Part 12 of 12)

Aphorism 6: The Surest Way to Get a Better Forecast is to Make the Demand Forecastable Forecast accuracy is largely dependent on volatility of demand, and demand variation is affected by our own organizational policies and practices. So an underused yet highly effective solution to the forecasting problem can be

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Analytics | Data Visualization

Mauricio GonzálezOctober 26, 2016 0

SAS 40 años impulsando cambios en la salud y el bienestar

En las últimas décadas la presencia de enfermedades como el cáncer, ha aumentado considerablemente a nivel mundial, sin embargo, hoy en día la tasa de éxito en los tratamientos es mayor de lo que era años atrás. Por ejemplo, en 1975 una persona diagnosticada con esta enfermedad tenía tan sólo

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Advanced Analytics | Analytics | Data Visualization

Suzanne ClaytonOctober 26, 2016 0

Digital transformation = increased expectations for media & entertainment

Consumers want content 24 hours a day, seven days a week, all around the world. It's a tall order for media & entertainment (M&E) companies and a 180 degree shift from days past. How do they provide enough content to meet demand? Audiences are binge watching over-the-top (OTT) programming, creating

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Sports & Entertainment

Advanced Analytics | Analytics

Mike GillilandOctober 26, 2016 0

Changing the paradigm for business forecasting (Part 11 of 12)

Aphorism 3: Organizational Policies and Politics Can Have a Significant Impact on Forecasting Effectiveness We just saw how demand volatility reduces forecastability. Yet our sales, marketing, and financial incentives are usually designed to add volatility. We reward sales spikes and record weeks, rather than smooth, stable, predictable growth. The forecast

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Advanced Analytics | Analytics

Megatrends im Analytics Bereich

Dr. Laurie MilesOctober 26, 2016 0

Results-as-a-Service - Aussagekräftige Analysen für alle!

In seinem Buch „Competing on Analytics“ benennt Tom Davenport die Analytik als Grundlage nachhaltiger Wettbewerbsvorteile. Der Grund dafür ist der prädiktive Ansatz. Heutzutage ist es nicht mehr möglich, ein Unternehmen alleine mit Blick in den Rückspiegel zum Erfolg zu führen. Und Analytik erlaubt den dringend erforderlichen Blick in die Zukunft.

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Analytics | Data Visualization

Robert AllisonOctober 25, 2016 0

The perfect storm for State Fair attendance!

The State Fair in North Carolina is just a few miles from SAS headquarters, and therefore it's virtually impossible for it to slip by without me noticing it. There are two aspects of the fair that usually get lots of news coverage - what's the latest fair-food, and did we

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Advanced Analytics | Analytics

Mike GillilandOctober 25, 2016 0

Changing the Paradigm for Business Forecasting (Part 10 of 12)

The Aphorisms of the New Defensive Paradigm I want to finish this blog series with a set of 7 aphorisms – concise statements of principle – that characterize the new Defensive paradigm for business forecasting. The first is that: Aphorism 1: Forecasting is a Huge Waste of Management Time This

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Analytics | Internet of Things

Michael ProbstOctober 25, 2016 0

Blogparade (#data4IoT) zum Internet der Dinge (IoT) - Machen Sie mit!

Das Internet of Things (IoT) hat es geschafft, raus aus der Expertennische zu sein. Heute wird es von Verbänden, Politik und eben auch vom Verbraucher diskutiert. Experten erwarten, dass das IoT bis 2020 den Mainstream-Status erreicht hat. Ist also alles dazu gesagt? Keinesfalls – jetzt wird die Diskussion erst richtig

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Analytics | Data Visualization

Robert AllisonOctober 24, 2016 0

How much does it cost to live to 100?

Living to 100 isn't as simple as just paying a certain amount of money for your healthcare. But that is an interesting aspect of longevity, so let's have a look at the data ... In my previous blog post, we analyzed how much people from various countries spend on healthcare.

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Advanced Analytics | Analytics

Mike GillilandOctober 24, 2016 0

Changing the paradigm for business forecasting (Part 9 of 12)

Academic Research In an approach akin to FVA analysis, Paul Goodwin and Robert Fildes published a frequently cited study of four supply chain companies and 60,000 actual forecasts.* They found that 75% of the time an analyst adjusted the statistical forecast. They were trying to figure out, like FVA does,

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Advanced Analytics | Analytics

FVA comparisons

Mike GillilandOctober 21, 2016 0

Changing the paradigm for business forecasting (Part 8 of 12)

Typical Business Forecasting Process Let’s look at a typical business forecasting process. Historical data is fed into forecasting software which generates the "statistical" forecast. An analyst can review and override the forecast, which then goes into a more elaborate collaborative or consensus process for further adjustment. Many organizations also have

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Analytics | Data for Good | Data Management

doctor looking at clinical data on tablet

David DowningOctober 21, 2016 0

How mature is your decision-making strategy?

In recent healthcare blogs I’ve looked at the need to drive more value from the UK’s National Health Service (NHS) and how this relies upon the ability to make decisions based on robust, data-driven insights. But what value will these decisions have if they're not founded on a mature data

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Advanced Analytics | Analytics

Mike GillilandOctober 20, 2016 0

Changing the paradigm for business forecasting (Part 7 of 12)

The Means of the Defensive Paradigm The Defensive paradigm pursues its objective by identifying and eliminating forecasting process waste. (Waste is defined as efforts that are failing to make the forecast more accurate and less biased, or are even making the forecast worse.) In this context, it may seem ridiculous

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Analytics | Customer Intelligence | Data Visualization

SAS ColombiaOctober 19, 2016 0

Analytics Everywhere: el caso de Ferrari

No cabe duda de que la analítica ahora está en todas partes. Gracias a la Nube (cloud) se puede acceder a las soluciones desde cualquier lugar y aplicarla en todo lo que nos imaginemos. Incluso en una pista tan sofisticada y tecnológica como resulta ser la de la Fórmula 1,

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Advanced Analytics | Analytics

Four alternative models

Mike GillilandOctober 19, 2016 0

Changing the paradigm for business forecasting (Part 6 of 12)

Why the Attraction for the Offensive Paradigm? In addition to the reasons provided by Green and Armstrong, I'd like to add one more reason for the lure of complexity: You can always add complexity to a model to better fit the history. In fact, you can always create a model

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Advanced Analytics | Analytics

Mike GillilandOctober 19, 2016 0

Guest blogger Len Tashman previews Fall 2016 issue of Foresight

Fresh from chairing the Foresight Practitioner Conference on “Worst Practices in Business Forecasting,” hosted two weeks ago at the Institute for Advanced Analytics at North Carolina State University, Foresight editor-in-chief Len Tashman previews the Fall 2016 issue. Preview of the Fall 2016 issue of Foresight In the provocative article, “The

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Advanced Analytics | Analytics

Mike GillilandOctober 18, 2016 0

Changing the paradigm for business forecasting (Part 5 of 12)

Implications for the Offensive Paradigm The worldview promulgated by the Offensive paradigm is that if we only had MORE – more data, more computational power, more complex models, more elaborate processes – we could eventually solve the business forecasting problem. But this just doesn’t seem to be the case. Operating

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Analytics | Data for Good | Data Visualization

Robert AllisonOctober 17, 2016 0

How much does each country spend on healthcare?

With the US Affordable Care Act (ACA) and other health topics in the news lately, I wondered how much people spend on healthcare in various countries. Of course spending varies from person to person, so I decided to take a look at the average per capita spending in each country (it's

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Analytics

Carl FarrellOctober 17, 2016 0

Always Open

Open. The very word evokes a sense of happiness and possibility. When you’re hungry at an odd hour and everything around you seems to be closed, that lone neon sign glowing in a restaurant window is a most welcome relief. When a shop or service you’ve longed for finally builds

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Advanced Analytics | Analytics

Mike GillilandOctober 17, 2016 0

Changing the paradigm for business forecasting (Part 4 of 12)

Is Complexity Bad? It’s necessary to point out that Goodwin’s article is not arguing against complexity per se, and I’m not either. When you have a high value forecast, where it is critical to be as accurate as possible, of course you are going to want to try every technique

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Analytics

Hadoop und BARC

Torsten BeckOctober 17, 2016 0

Hadoop und Data Lakes – Use Cases, Nutzen und Grenzen

Die aktuelle BARC-Studie verrät die Sicht der Unternehmen auf modernes Datenmanagement mittels Hadoop und Data-Lake-Konzepten. Die Anwenderbefragung gibt einen interessanten Blick auf den derzeitigen Status von Hadoop und Data Lakes in Europa und Nordamerika. Wo wird das Ecosystem eingesetzt, was ist der erhoffte Nutzen, und wo sind die Grenzen, um

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Advanced Analytics | Analytics

Mike GillilandOctober 14, 2016 0

Changing the paradigm for business forecasting (Part 3 of 12)

Anomalies: The Beginning of a Crisis While even trained scientists can fail to see things that fall outside what they are looking for, anomalies eventually start to get noticed. But still, for a long time, anomalies within an existing paradigm are seen as mere “violations of expectation.” The response within

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Analytics

John GreenOctober 14, 2016 0

Not your father’s IT Department

Today’s IT department isn’t your grandfather’s IT department. It’s not even your father’s IT department. When people talk about Information Technology Departments of the past, it's usually broken into three distinct periods: The Mainframe; PCs; the Internet/post PC. The IT department was seen as the hardware support arm of an

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Analytics

Olivier PenelOctober 14, 2016 0

Big Data Governance: 5 Tipps für erfolgreiche Big-Data-Initiativen

Das ist der dritte Beitrag zur Blog-Serie Big Data Governance. Bisher sind erschienen Wie Big Data Unternehmen durcheinanderwirbelt und Mit Data Governance gegen den Datensumpf. Zum Abschluss möchte ich 5 Tipps abgeben, die ich selbst von Pionieren in Sachen Big Data übernommen habe. Meine erste Empfehlung lautet, Data Governance bereits zu Beginn der

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Advanced Analytics | Analytics

Gorilla Experiment Video

Mike GillilandOctober 13, 2016 0

Changing the paradigm for business forecasting (Part 2 of 12)

The Current Paradigm for Business Forecasting So what is the current paradigm that we, the community of business forecasting practitioners and researchers, are operating under? I’d argue that for at least the last 60 years, since 1956 when Robert G. Brown published his short monograph Exponential Smoothing for Predicting Demand,

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Analytics | Data for Good

Will JonesOctober 13, 2016 0

Taking a “Moneyball” approach to child welfare workforce woes

Could you imagine running a business with a 35-90% annual turnover rate? What if the average time to fill a position was anywhere between 3-12 months? This alone would cripple most organizations, but is a common reality in state and local child welfare agencies. High turnover and vacancy rates are

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