In Part I of this blog post, I provided an overview of the approach my team and I took tackling the problem of classifying diverse, messy documents at scale. I shared the details of how we chose to preprocess the data and how we created features from documents of interest
Unstructured text data is ubiquitous in both business and government and extracting value from it at scale is a common challenge. Organizations that have been around for a while often have vast paper archives. Digitizing these archives does not necessarily make them usable for search and analysis, since documents are
As an example, when using ordinary least squares regression (OLS), if your response or dependent attribute’s residuals are not normally distributed, your analysis is likely going to be affected and typically not in a good way. The farther away your input data is from normality, the impact on your model
SAS' Fijoy Vadakkumpadan, a computer vision expert, sheds light on how loadImages works in SAS Viya.
Vivimos una crisis sin precedentes en nuestra historia. A causa del COVID-19, numerosos países han impuesto diferentes medidas de cuarentena y restricciones a la vida social y económica. La salud es la prioridad , pero se han puesto en marcha múltiples ayudas con objeto de paliar la inmediata crisis económica.
Damit Innovation in Disruption umbenannt werden kann, braucht es erst mal ein gutes Ohr für das noch theoretische Vorhaben.
분석은 왜, 전사적으로 활용되지 못할까요? 최근 맥킨지 연구에 따르면 AI와 분석을 전 세계 산업 전반에 적용할 경우, 약 9조~15조 달러의 가치 창출이 가능합니다. 그런데도 오직 8%의 주요 기업만이 전사적으로 분석을 활용하고 있습니다. 무려 90% 이상의 기업이 분석을 조직의 모든 영역으로 확산하지 못하고 있는 것입니다. 조직 내 분석 확산과 관련하여 주요 관계자들은 각기 다른 고민을 안고 있습니다. ▶IT리더는 제한된 비용으로 신기술을 적용하고 혁신을 이루어야 합니다. 한편으로는 끊임없이 개발 및 변경되는 분석 모델을
El texto no estructurado es la mayor fuente de datos generada por el ser humano y crece exponencialmente cada minuto. No hay que olvidar que la tecnología está ya presente en todos los aspectos de nuestras vidas, tanto profesionales como personales, y nos permite conversar rápidamente a través de textos,
One of the questions we hear a lot about artificial intelligence is, “Which algorithm or AI technique should I use?” For complex problems, the answer isn’t always one technique or another. Instead, the best answer to any problem is often a combination of multiple techniques and technologies. We’re seeing with
In my 25 years in the data and analytics arena, I’ve had the good fortune to work across many sectors. Historically within the private sector, but more recently with the public sector. With digital transformation firmly on the agenda, public sector bodies are leading the way in many ways in
Na sessão Risk Modernization: Risk Analytics Model Life Cycles on SAS® Viya® , Stefano Biondi, diretor de risco do grupo italiano Banca Mediolanum, falou sobre sobre a modernização dos processos de desenvolvimento de modelos de risco de crédito e mercado usando ferramentas do SAS, especialmente o SAS Viya. O uso
Decision trees are one of the top machine learning algorithms used by data scientists. Decision trees use supervised learning to classify problems. Even if you are not a data scientist, chances are you can interpret the visual output from a decision tree.
The 10th edition of this series puts the spotlight on two organizations at which I had the pleasure of helping to teach students the humble beginnings of data, analytics and data visualization: Avans and HAN (Hogeschool van Arnhem en Nijmegen). My sources for this post are Gerben Muller, who initially
I think one of the great uses of analytics and graphics is to show things like cancer clusters on a map. There are many factors that can lead to a higher incidence of diseases in geographical areas, and chemicals are often the culprit. For example, paraquat has been potentially linked
With the release of SAS Viya 2020.1.4, text categories and concept models can now be deployed into production with just a few clicks and used to score data in-batch and via API! You can also now use these models in decision flows.
Machine Learning models are becoming widely used to formulate and describe processes’ key metrics across different industry fields. There is also an increasing need for the integration of these Machine Learning (ML) models with other Advanced Analytics methodologies, such as Optimization. Specifically, in the manufacturing industry, SAS explored state-of-the-art science
Chatbots offer another user-friendly conversational interface to the entire SAS Viya ecosystem, bringing together reporting capabilities, analytics and artificial intelligence.
I recently learned about a new feature in PROC QUANTREG that was added in SAS/STAT 15.1 (part of SAS 9.4M6). Recall that PROC QUANTREG enables you to perform quantile regression in SAS. (If you are not familiar with quantile regression, see an earlier article that describes quantile regression and provides
A key component to make sure that we develop responsible AI is diversity. This is because an AI application reflects and even amplifies the biases of its developers. As I discussed in my previous post, a diverse team will see things from many different points of view and help to
Data scientist has been on the career hot list for years, but how does one become a data scientist? Well, my journey to becoming a data scientist was not an intentional journey - I didn't start with a plan to end up in a data science career. In fact, I
Curiosity means asking questions, digging in. It’s what allows us to make progress on some of the world’s most pressing problems – obstacles that can sometimes feel too big to solve. When it comes to these complex problems, where do you begin? At SAS, we start at the crossroads between
Note from Udo Sglavo on mathematical optimization: When data scientists look at the essence of analytics and wonder about their daily endeavor, it often comes down to supporting better decisions. Peter F. Drucker, the founder of modern management, stated: "Whenever you see a successful business, someone once made a courageous decision."
The Smart Cities movement continues to forge ahead and evolve, led by innovative municipalities of all sizes. One of the towns at the forefront is Cary, North Carolina, adjacent to the Research Triangle Park and home of the SAS world headquarters. Cary Chief Information Officer Nicole Raimundo and her team
A note from Udo Sglavo: This post offers an introduction to complex optimization problems and the sophisticated algorithms SAS provides to solve them. In previous posts of this series, we learned that data availability, combined with more and cheaper computing power, creates an essential opportunity for decision-makers. After looking at network analytics
The infinite game-changer to monetize your analytics opportunities Does your factory still belong to the minor 11 percent saying that 5G is not on your radar? This means your factory is not planning to realize benefits from use cases like remote predictive maintenance, time-critical process optimization, automated visual quality inspection,
A note from Udo Sglavo: A wealth of connectivity is pervasive in the data we gather across many industries. In other words, networks are all around us. A data science trend you cannot ignore is to organize, learn from, and drive decision-making based on connected data. Network analytics engines provide efficient
“It doesn’t stop being magic just because you know how it works.” Terry Pratchett, The Discworld Series Welcome to the third, and final, installment of Data Science in the Wild. In Part 1 we were lost in the woods thinking about how to start a data science project. In Part
Conversational AI can offer a way to provide that always-on 24/7, fast, convenient experience that can go anywhere (phone, computer smart speakers, even your car). It can provide a human-like experience through real-time, personalized interaction with AI running in the background. This technology is being applied across many industries for a variety of use cases (both customer-facing and for internal use).
A year ago we could not imagine stadiums being empty during the most exciting sports events, but it is a common sight now. The entertainment sector is one of the hardest hit sectors because of the COVID-19 pandemic [1]. Social distancing requirements made it impossible to have viewers in stadiums
Here is the second installment of the 3-part series by guest bloggers Jessica Curtis and Andrea Moore. (If you missed it, here is Part 1.) THE VALUE SAS DELIVERS TO OPEN SOURCE First and foremost, SAS distributes the input data for forecasting. SAS knows how to split up data intelligently
