Co analityk może zrobić lepiej w swojej codziennej pracy, aby uzyskać lepsze rezultaty. Jakie działania przyczyniają się najczęściej do tego, że wynik pracy analityka jest daleki od optymalnego. Spróbuję przybliżyć odpowiedzi na te pytania, skupiając się głównie na obszarze Customer Intelligence, choć wiele z tych problemów pojawia się również w
SAS Explore was created by technologists for technologists, and has more than 100 free SAS training sessions. Here are a few top picks!
For Christmas 2021, I wrote an article about palettes of Christmas colors, chiefly shades of red, green, silver, and gold. One of my readers joked that she would like to use my custom palette to design her own Christmas wrapping paper! I remembered her jest when I saw some artwork
One of the benefits of social media is the opportunity to learn new things. Recently, I saw a post on Twitter that intrigued me. The tweet said that the expected volume of a random tetrahedron in the unit cube (in 3-D) is E[Volume] = 0.0138427757.... This number seems surprisingly small!
Crises like the COVID-19 pandemic have increased the demand for public health experts who possess advanced analytics skills. After all, data – when properly collected, analyzed and understood – has immense power to inform decision-making. And in areas like public health, informed decision making can save lives. Azhar Nizam has
You’re down by 10 points in your NFL fantasy football league, and you need to choose a wide receiver from the free agency pool because your starter was injured. How do you decide to get the 11 points required for a win? What methods will you use to lead you
Consumers are pulling back and shifting their purchases in the wake of inflationary pressures caused by high prices for fuel, freight costs, consumer goods and nonessential products. Demand is shifting faster than many retailers and consumer goods companies anticipated. Inflation continues to rise forcing consumer spending to shift once again
Robert Handfield, PhD, is a distinguished professor of Supply Chain Management at North Carolina State University and Director of the Supply Chain Resource Cooperative. In an episode of the Health Pulse Podcast, Handfield gave his views regarding the challenges health care and life science companies have encountered over the past two years
Wouldn’t it be cool if we establish a mechanism that provides more data scientists easy access to SAS Reinforcement Learning capabilities, from a centralized location and using a standardized approach?
SAS has been extending technological boundaries for many years. Whether in analytics, artificial intelligence (AI) or cloud, it excels in innovating what these technologies can do on a day-to-day basis. Recently, SAS released some of its most exciting announcements, sharing what is to come over the next couple of years.
M estimation is a robust regression technique that assigns a weight to each observation based on the magnitude of the residual for that observation. Large residuals are downweighted (assigned weights less than 1) whereas observations with small residuals are given weights close to 1. By iterating the reweighting and fitting
Robert Blanchard's role as a data scientist at SAS has afforded him the flexibility to live where he wants, in his case, on a beach in San Diego.
One thing that impresses me about the analytical solutions we have is the degree of granularity we can get down to in the forecasting & planning process.
SAS' Ricky Tharrington and Jagruti Kanjia explain two ways bias shows up in model predictions.
Change is the only constant, and it doesn’t happen overnight. This is particularly true in the world of data analytics. As organizations are looking to become more digital, resilient and profitable, executives are going back to the whiteboard to reconsider how they’re using data and analytics to transform their business.
The concept of a "data-driven company" is widely promoted and discussed today. Are executives looking to invest in analytics and see an added value? Do many decision makers first analyze whether this investment simply pays off? This article is the first in a series on the practical application of analytics
Longitudinal data are measurements for a set of subjects at multiple points in time. Also called "panel data" or "repeated measures data," this kind of data is common in clinical trials in which patients are tracked over time. Recently, a SAS programmer asked how to visualize missing values in a
Did you know that you can use π to partition the positive integers into two disjoint groups? It's not hard. One group is generated by the integer portions of multiples of π. The FLOOR function gives the integer portion of a positive number, so you can write integer that are
Let's take a look at the design and implementation of SAS functions in financial calculations. We'll do this through examples calculating and analyzing the monthly payment, interest, and principal for CPM/CAM mortgages.
I'm not sure when it started, but I've had this lifelong situation that began small, I'm sure, and then grew! While I've encouraged it to become a friend, some days it is not. You may ask who or what this friend is. It's a little thing called perfectionism. It can
The social and economic impact of COVID-19 has dramatically affected supply chains and demand planning across all industries. Then there’s the Amazon effect, which has led to sky-high consumer expectations of the ordering and delivery process. Demand planners for retailers and consumer goods companies have quickly realized they have no
During lockdowns across Europe and beyond, we all moved our lives online. We worked remotely and had meetings via Teams or Zoom. We also socialised and shopped online. For many people, this was familiar territory. For others, it opened up a whole new world—and highlighted significant problems with the ‘old
Demand management concepts are now over 30 years old. The first use of the term "demand management" surfaced in the commercial sector in the late 1980s and early 1990s. Before that, the focus was on a more siloed approach to demand forecasting and planning that was manual and used simple
In this Q&A with MIT/SMR Connections, Gavin Day, Senior Vice President of Technology at SAS, shares real-life examples of artificial intelligence (AI) at work, discusses picking the right problems to solve with AI, dispels a common misconception about AI, and defines AI success. Q: Could you describe some especially interesting
Stephen Hawking, el afamado físico inglés, pronosticó hace años lo siguiente: "Cada aspecto de nuestras vidas será transformado por la Inteligencia Artificial (IA). Este podría ser el evento más grande en la historia de nuestra civilización". Este futuro finalmente es ahora una realidad. En un artículo publicado por Julia Brodsky
In a world increasingly characterized by digital economies and disruption, every market disturbance exponentially widens the business agility gap between the less digitally evolved and those companies that have demonstrated innovation leadership through digital transformation. For those that are not transforming with urgency, the negative consequences will become compounded to
I am gratified to see the continuing adoption of Forecast Value Added by organizations worldwide. FVA is an easy to understand and easy to apply approach for identifying bad practices in your forecasting process. And I'm particularly gratified to see coverage of FVA in two new books, which the authors
Last week Len Tashman, Udo Sglavo and I announced release of our new collection: Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning. Today, we share an excerpt from the book, one of the sixteen opinion/editorial "Afterwords" contributed by influential leaders in academics and industry, this one by
Data, AI and digital transformation will define the industry of the future. The die is cast. Without an industrial approach for analytics, there will be no future! Diamonds are forever Khepri, a deity of ancient Egypt, symbolized the morning rebirth of the sun. Khepri is also said to have inspired
In the first of two posts spotlighting SAS R&D innovators, SAS' Udo Sglavo introduces you to developers Amy Shi, Maggie Du and Phil Helmkamp.
