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Advanced Analytics

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Advanced Analytics

Jonathan ZenoudaDecember 9, 2016 0

Enhancing SAS Asset Performance Analytics’ Root Cause Analysis with Calculated Columns

During a recent customer visit, I was asked how to include a calculated variable within SAS Asset Performance Analytics’ (APA) Root Cause Analysis workflow. This is a simple request. Is there a simple approach to do this? To remind you, in the APA workflow, an ETL Administrator makes a Data

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Advanced Analytics | Analytics | Data Management

Christian EngelDecember 8, 2016 0

IDV: Banken müssen Spagat zwischen Flexibilität und Governance schaffen

IDV (Individuelle Datenverarbeitung) ist ein Thema, das in den Banken als Teil von BCBS 239 seit Langem kritisch diskutiert wird. Ruppert Jaeschke betreut und berät seit fast 15 Jahren zahlreiche deutsche Banken im Umfeld Business Intelligence und SAS. Er hat eine klare Meinung zu diesem regulatorischen Thema. Frage: Welche Schmerzen

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Banking | Government

Advanced Analytics | Analytics | Internet of Things

Rainer SterneckerDecember 7, 2016 0

#postfaktisch #postdata #postanalytics

Wir alle müssen jetzt ganz stark sein. Und mit „wir“, da meine ich alle Vertreter der Informationstechnologie. Vom Anwender, Datenbankadministrator, bis hin zum Techniker, der das Netzwerkkabel anschließt. Wir können jetzt nämlich alle zusammenpacken und nach Hause gehen! Ja, jetzt ist soweit! Wir wurden enttarnt. Sie glauben mir nicht? Dann

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Advanced Analytics

Rick WicklinDecember 7, 2016 0

Simultaneous confidence intervals for a multivariate mean

Many SAS procedure compute statistics and also compute confidence intervals for the associated parameters. For example, PROC MEANS can compute the estimate of a univariate mean, and you can use the CLM option to get a confidence interval for the population mean. Many parametric regression procedures (such as PROC GLM)

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Advanced Analytics

Muhammad Asif AbbasiDecember 1, 2016 0

SAS integration with Hadoop - one success story

Nearly every organization has to deal with big data, and that often means dealing with big data problems. For some organizations, especially government agencies, addressing these problems provides more than a competitive advantage, it helps them ensure public confidence in their work or meet standards mandated by law. In this

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Advanced Analytics | Data for Good | SAS Events

Polly Mitchell-GuthrieNovember 29, 2016 0

4 tips to ensure your data4good efforts have an impact

In honor of today’s #GivingTuesday, which "harnesses the potential of social media and the generosity of people around the world to bring about real change in their communities,” I’ve been thinking about what constitutes “real change” and the role analytics can play on the many social issues our planet faces.

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Advanced Analytics

Ed HughesNovember 10, 2016 0

SAS at the 2016 INFORMS Annual Meeting

The 2016 INFORMS Annual Meeting will be held at the Music City Center and Omni Nashville Hotel in downtown Nashville, TN on November 13-16, with pre-conference events starting on Saturday, November 12. SAS will be a major participant in this conference. Over two dozen people from SAS will attend, with

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Advanced Analytics

David FredeOctober 27, 2016 0

How to maximize manufacturing production assets

I've been reflecting on my life and career recently and was amazed to discover that I just hit 30 years of working with industrial and manufacturing applications. While it’s a bit tough to admit my age, I’m quite happy with my career and have enjoyed manufacturing and industrial applications. I

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Manufacturing

Advanced Analytics | Analytics

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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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

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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Advanced Analytics | Fraud & Security Intelligence

Stavros StavrinoudakisOctober 25, 2016 0

A practical guide to tackle auto insurance fraud - Part 3: Advanced Analytics

This is the third of the seven parts of blog post series “A practical guide to tackle auto insurance fraud”. In the first two articles of the series we drilled down to Data Management and Data Quality as the basis for insurance fraud detection analytics and also to the Business

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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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Advanced Analytics | Data Management

David PopeOctober 24, 2016 0

Analytics: Four key elements for success

Analytics provides better insights into why something happened, or helps provide decision makers with information about what will happen in the future. That allows organizations to act now to improve outcomes instead of reacting to events after they happen. But it takes more than analytics alone. Achieving this level of

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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

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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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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Advanced Analytics | Analytics

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

Rick WicklinOctober 19, 2016 0

Loess regression in SAS/IML

A previous post discusses how the loess regression algorithm is implemented in SAS. The LOESS procedure in SAS/STAT software provides the data analyst with options to control the loess algorithm and fit nonparametric smoothing curves through points in a scatter plot. Although PROC LOESS satisfies 99.99% of SAS users who

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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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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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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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Advanced Analytics | Analytics

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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Advanced Analytics | Analytics

Mike GillilandOctober 13, 2016 0

Changing the paradigm for business forecasting (Part 1 of 12)

In a February 2015 post Offensive vs. Defensive Forecasting, I sought to distinguish two very different approaches to the business forecasting problem: Offensive: The "offensive" forecaster is focused on forecast accuracy -- on extracting every last fraction of a percent of accuracy we can hope to achieve. The approach is

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Advanced Analytics | Analytics

Mike GillilandSeptember 27, 2016 0

NIJ crime forecasting challenge

NIJ's Real-Time Forecasting Challenge If you want to show off your forecasting chops, and maybe even make a little money, the National Institute of Justice has just the challenge for you. The NIJ's Real-Time Crime Forecasting Challenge: ...seeks to harness the advances in data science to address the challenges of

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Advanced Analytics | Machine Learning

Patrick KochSeptember 20, 2016 0

Local Search Optimization for HyperParameter Tuning

When shopping for a new TV, with many sets next to each other across a store wall, it is easy to compare the picture quality and brightness. What is not immediately evident and expected is the difference between how the set looked in the store and how it looks in your

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Advanced Analytics | Fraud & Security Intelligence | SAS Events

SAS PolandSeptember 15, 2016 0

SAS® Visual Investigator – nowy wymiar użycia zaawansowanej analityki SAS

W obecnych czasach temat wykrywania nadużyć w obszarach finansów, usług dla obywateli oraz bezpieczeństwa narodowego staje się coraz większym wyzwaniem dla firm prywatnych i instytucji państwowych. Powszechność dostępu do Internetu, gwałtowny rozwój handlu elektronicznego i rosnące ilości danych przetwarzanych w usługach „w chmurze” powodują konieczność zastosowania zaawansowanych narzędzi informatycznych. SAS®

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