Developer papers from SAS Global Forum 2020 - Updated
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Since I originally published this article, several papers I highlighted now have accompanying videos. I updated the table with links to the videos, where applicable. Take another look and see you on June 16!
I was excited this week to see the SAS Global Forum 2020 Proceedings published. I accessed the web site and see scores of great papers. There is Search capability and various filters offered; however, it can still be challenging to pinpoint the exact article(s) you want to explore.
I went through proceedings and have identified a list of papers I plan on reading and may interest open source developers, data scientists, and application developers. I performed searches on 'APIs', 'open source', 'Python', and 'R programming' and handpicked from those searches. The list below is far from exhaustive. If you feel there's something missing, please comment and I can update as needed.
| Title | Abstract |
| The main goal of this article is to propose, describe, explain, and discuss an original idea of a process and tools required to build SAS packages. In subsequent sections we introduce the concept of a SAS package from both user and developer point of view. |
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| Automatically Loading CAS Tables from SAS® Data Integration Studio Using SAS® Viya® REST APIs | The focus of the solution proposed in this paper will be on updating CAS tables automatically, for a given set of reports within a particular folder (and the folders that are under that), through the use of SAS® Data Integration Studio and SAS® Viya REST API. This integration is fully achievable by any other team, company or organization, using the same tools and with a few lines of SAS® code. |
| A Beginners Guide to Consuming RESTful Web Services in SAS® | This paper presents how web services can be consumed in SAS. It will explore the PROC HTTP and discuss the dif ferent options that must be set correctly to consume a web service. It shows how parameters can be generated f rom existing SAS data using PROC STREAM and can be submitted when calling a web service. And finally, it describes how the output from a web service can be read into SAS using the JSON and XML libname engine. |
| Ten Minutes to Your First Hello World: REST APIs | The objective is to facilitate your time to first Hello World (TtFHW) with the SAS Viya REST APIs so that the process is seamless and simple. Accompanying this paper is a Jupyter based playbook that works out of the box with SAS Viya, uses Jupyter for the interface, and follows a standard workflow. The playbook is used to demonstrate a generally accepted practice in order to prepare an Analytical Base Table (ABT). Analysts typically denormalize the data and create statistically relevant columns when creating an ABT. The resulting ABT can then be used for subsequent analysis and modeling in SAS Viya. |
| Real-time call analytics using SAS® Viya® and open source platforms | Objective of this paper is to analyze customer audio transcripts between agents and customers to better understand real-time customer/agent responses and measure customer satisfaction using SAS Viya audio translator and Visual Text Analytics/EM Text Mining. This project will establish a foundation to leverage SAS VIYA and REST API- Python SWAT package on a real-time basis for accelerated insightful agent recommendations. |
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SAS® Visual Analytics SDK: Embed SAS Visual Analytics Insights in Your Web Pages and Web Apps |
This paper presents an overview of the SAS® Visual Analytics SDK and provides the details you need to begin publishing your SAS® Visual Analytics insights in your custom web pages, web apps, and portals. First you will learn the configuration changes needed for SAS® Viya®. Just minor tweaks, but these modifications are required to allow the SAS Visual Analytics SDK to access your report content. |
| REST Just Got Easy with SAS® and PROC HTTP | The HTTP procedure has been a staple in SAS for many years for communicating with the web and Representational State Transfer (REST) APIs. Over the past few years, PROC HTTP has seen many updates that continue to increase its functionality and usability. SAS® Viya 3.5 continues this trend by introducing some new syntax to the procedure that makes many common tasks simpler as well as more accessible to newer SAS developers who might be used to other HTTP frameworks. |
| Using SAS9API and R to Create Violin Plots, Interactive 3D Plots, and a Shiny App for SAS® Data Sets | Open-source tools are extremely popular within the data science community and R language is one of them. While SAS Viya allows easy collaboration between SAS and open-source languages like R and Python using HTTP protocol, SAS9 lacks this feature. To address this issue we at Analytium designed our SAS9API solution. It is based on REST API and allows you to connect to your SAS server. With SAS9API help you can get and manage SAS data and metadata. We created a wrapper R package rsas9api. Among other options, it allows loading SAS data into R. |
| RSUB, CLI for SAS® Server Environments | RSUB is a command line interface, written in Java, which takes advantage of SAS Integration Technologies to fill a gap in SAS 9. Creating the RSUB utility fulfilled the needs of users, providing them a CLI to use for batch processing and scheduling in third party enterprise schedulers. It allows you to start a SAS session, submit a program and retrieve logging and listing outputs in return. This paper aims to describe the RSUB utility, its features and usage. Additionally, we will use it to explore topics common to using SAS Integration Technologies Java API for developing similar projects. |
| Building HTML5 apps is now easier than ever, thanks to the growth of open source tooling designed to work specifically with SAS. This paper will walk through some examples of building web apps, and provide a bunch of tips & tricks along the way. | |
| Choose Your Own Adventure: Manage Model Development via a Python IDE | This paper introduces the new sasctl package for Python, designed to allow control of the SAS® Viya® platform from a Python runtime. It can be used as a Python module or executed directly from a command line interface. We first demonstrate how to use sasctl for managing model registration and deployment of both SAS and open-source models. Then, we introduce additional functionality such as monitoring model performance and rendering visualizations. |
| How to Build a Text Analytics Model in SAS® Viya® with Python | This paper highlights the construction of an end-to-end text analytics model that leverages CAS actions called from Python. It demonstrates how the unstructured text of Amazon reviews can be converted into structured input variables and used in a Support Vector Machine (SVM) model to predict whether users will find an Amazon review helpful. The client-side platform used is a Jupyter notebook, a very popular interface for Python users. |
| SAS® Model Manager is evolving to be a management platform that handles traditional SAS models and open-source models as equal partners. This paper discusses strategies for managing the life cycles of Python, R, and TensorFlow models using SAS Model Manager. | |
| Using Python with Model Studio for SAS® Visual Data Mining and Machine Learning | The paper discusses specific ways in which open source software is embraced within SAS Viya. Python, a popular open source scripting language, is used to illustrate how you can integrate and use open source technology within Model Studio for SAS® Visual Data Mining and Machine Learning software. |
| Open Source Python & R Lang on our SAS Shared Grid | This paper gives an insight into the process we experienced when introducing Open Source Python & R Lang onto our SAS Platform. |
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Scalable Cloud-Based Time Series Analysis and Forecasting Using Open-Source Software |
This paper provides an overview of the SAS Visual Forecasting procedures—in particular of the TSMODEL procedure, which was specifically designed to support advanced, efficient, and cloud-based time series analysis of big data. Particular emphasis is given to integrating Python and R code with PROC TSMODEL in order to enable efficient, massively parallel execution of Python and R programs. |
| The History and Evolution of SASPy, Including an Overview of What It Can Do and How to Use It | This session blends in this insight while giving an overview of SASPy, including the various ways it can connect to your different SAS installations, how to configure it for each one, a walk-through of the core functionality, and a look at some of the more advanced features. The goal is that you end up with a much better understanding of how to use SASPy to accomplish even better combined Python and SAS workflows for your projects. |
| How to Make Your First Impressive Web Application with Stored Processes and a Web Browser | SAS® has provided the Stored Process Web Application that lets us connect the web browser to the SAS server, which opens up an enormous range of potential applications. In the simplest form, we can use a stored process to prompt the user for some info, run SAS code using that info, and return results to the web browser. From this simple starting point, this paper shows you how to make a more powerful and flexible web application. |
| Creating Custom Web Applications with SAS® Viya® Jobs | The agenda for this session includes the following topics: what a SAS Viya job is; how to create and register a job in SAS® Studio; how to associate a form with a job for parameter selection; incorporating HTML into your job; and creating a full-blown web application by using jobs. |
| SAS® Enterprise MinerTM vs. Scikit-Learn – How do they recommend me good songs? | In this scenario, we will develop two Recommender Systems, first one using SAS® Enterprise Miner and another one using Python-Scikit-Learn, and evaluate theaccuracy of both modelling tools, and the results were amazing! |
| Risk Modeling on the Fast-Track: Pythonistas (and Others) Harness the Power of the SAS® Risk Engine | In this paper, we demonstrate the power of developing risk applications in Python based on the SAS Risk Engine with examples from both market and credit risk. |
| Behind the Front Door: Authentication Options with SAS® Viya® | If you are tasked with deploying and administering SAS® Viya®, one of your top concerns is how users will be authenticated. Will you use an LDAP directory, or is there a requirement to implement single sign-on with your company's existing security inf rastructure? Learn what the authentication options are in SAS Viya 3.5 and what information you need to obtain f rom your IT security department to configure them. Learn how to limit concurrent logins and see examples of how to customize the login page. |
| SAS® Cloud Analytic Services Sessions: Understanding Connection Options to Ensure Data Access Securi... | In SAS® Viya®, there are a variety of ways to connect to the SAS® Cloud Analytic Services (CAS) analytics engine, or CAS server. The resulting CAS sessions might run under the CAS instance's service account or the end user's identity. This is further complicated by whether the CAS client is using the Kerberos authentication protocol, which results in differences, depending on whether CAS is running on Linux or Windows. Understanding the default CAS session behavior for each application and how those defaults can be overridden and engineered to support data access policy is the focus of this paper. |
| NLP with BERT: Sentiment Analysis Using SAS® Deep Learning and DLPy | Bidirectional Encoder Representations from Transformers (BERT) combines language model pretraining and the Transformer architecture to achieve impressive performance on an array of NLP problems. Subsequent sections present an overview of BERT and a tutorial on how to build and train a BERT model using SAS Deep Learning actions and DLPy. |
| From state-of-the-art research to routine analytics, the Jupyter Notebook offers an unprecedented reporting medium. Traditional reports become dynamic documents that include both text and living SAS®, R, Python or other code that is run during document creation. With Jupyter, you have the power to create these computational narratives and much more! | |
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CASL, a Language Specifically Designed for Interacting with SAS® Viya® |
Allow me to introduce you to a very powerful language that is simple to use. CASL is a language designed to run SAS® Cloud Analytic Services (CAS) actions and process responses to generate a report. To make it easy for SAS users, the language syntax mimics the syntax of the DATA step. CASL is not just a language, but a programming environment that is embeddable into any program. CASL has one goal in mind, and that is to allow you to run actions in CAS and to process the results of those actions into useful data and sophisticated reports. |
| This paper demonstrates how to perform those common tasks with CASL. Understanding how to perform common tasks and having the code to do them empowers you to develop CASL programs and take full advantage of the CAS server. |
