Altair® SmartWorks™ Analytic: Empowering Everyone to Make Augmented, Data-driven Decisions

Risk assessment is crucial for any enterprise that extends credit to customers. Commonly known as credit scoring, the process helps lenders make confident, informed decisions on whether prospective customers will honor their debt. Credit scoring is typically associated with the banking and financial service sectors, but is required across a wide array of businesses, including telecoms, retail, and insurance. In most cases, credit scoring isn’t just a business tool, it’s a regulatory necessity. And credit scoring is a vast industry. In the U.S. alone, recent consumer debt valuations hover over $14 trillion. Credit scoring is a complex task that involves wrangling a diverse range and large volume of data. Based on predictive modeling, the use of artificial intelligence (AI) and machine learning (ML) is well established and widespread. And because of the data burden, credit risk firms were some of the earliest organizations to adopt the technology. As such, the credit risk sector can claim to be a pioneer in AI and ML utilization.

To successfully operationalize machine learning (ML) algorithms, data science teams must be able to continuously update their models so they can improve their predictive performance. The champion/challenger approach is a well-documented method for optimizing models and making adjustments that accounts for changes in the nature and quality of data inputs. Altair’s ML products make it easy to incorporate champion challenger processes into data analytics workflows.

Smart ecosystems span a variety of industries, technologies, and applications. They provide the backbone for operational innovation, efficiency, futureproofing, sustainability, and autonomy. Smart ecosystems harness the convergence of many technologies, and generally utilize data gathered from multiple sources to optimize operations, processes, systems, and products. The evolving built-to-specs smart energy management ecosystem is a prime example of technology convergence – it maximizes artificial intelligence (AI), data analytics, and Internet of Things (IoT) technology create sustainable energy platforms. These smart platforms are more efficient when generating, distributing, and using energy, which brings them closer to net-zero emissions and reduces their environmental footprint.

Learn about the different ways to deploy machine learning models using Altair® SmartWorks™ Analytics.

Users can begin making predictions after their machine learning models are registered and deployed in the SmartWorks Analytics MLOps application. This video explains how to send requests for predictions to a model using a Python script. Empower everyone to make augmented, data-driven decisions. See how with SmartWorks Analytics.

This series of short videos will help you understand the basics of data science. In Part 1, we focus on predictive analytics, which is the process of training computers with historical data so they can make accurate predictions. Click here to learn more about machine learning.

This is part two in a series of short videos to help you understand the basics of data science. This video focuses on the concepts of supervised and unsupervised learning. In supervised learning, you develop algorithms that predict outcomes based on independent variables and you use historical data to train your algorithms. Unsupervised learning models identify hidden patterns in your data and group records into clusters; they act on the dataset without human guidance. Click here to learn more about machine learning.

This is part three in a series of short videos to help you understand the basics of data science. This video focuses on prescriptive analytics, which uses results from multiple machine learning algorithms to inform future decisions. With prescriptive analytics, the object is to optimize and, to some extent, automate the decision-making process. A prescriptive analytics workflow can use multiple algorithms to prescribe actions based on the characteristics of new data. Click here to learn more about machine learning.

Explore MLOps with Altair® SmartWorks™ Analytics MLOps is a set of tools and processes that automate and streamline machine learning model deployments. When compared with conventional software production systems, MLOps saves time for data scientists, lowers system cost, and minimizes risk by managing code, artifacts and data in a reliable and reproducible way.

Knowledge Studio makes it easy to export models to Altair’s SmartWorks Analytics for model management and model deployment. This video was produced using Knowledge Studio 2021.3 and SmartWorks Analytics 2021.3.

Discover how Altair delivers an end-to-end platform that enables you to combine enterprise expertise with data and AI to build analytics applications and scalable automation – with or without code. Solving challenges in where multiple teams and skillsets are required to bring an AI and analytics project across the finish line. This breakout session by Sabina Stanescu, Senior Director, Product Management, Data Analytics, Altair, was presented at Future.AI in June 2021, and is about 20 minutes long.

IoT-enabled infrastructure in factories produce mountains of data that managers can use to optimize plant operations. IoT technology and the sensors that generate most of this data are key building blocks for executing on the industry 4.0 vision of a smart factory. The proper analysis and visualization of this data, coupled with machine learning deployed in the cloud or at the edge, can help companies achieve higher degrees of productivity, flexibility, and innovation and compete more effectively. The need to stitch together the tools required to support the entire workflow — from data prep to machine learning and MLOps (machine learning model operationalization management) — requires broad specialized knowledge and expertise, as well as significant upfront investment. Coupled with the need for data to pass between systems and tools, these factors introduce substantial amounts of risk into the implementation process. We built Altair® SmartWorks™ Analytics specifically to address these challenges and enable data-driven decision making and AI-augmented automation. In this video, we demonstrate how to build an analytics pipeline, including deployment of MLOps models, in a smart factory environment.

Altair® SmartWorks™ Analytics is an end-to-end platform that enables you to combine enterprise expertise with data and artificial intelligence (AI) to build analytics applications and scalable automation – with or without code.

Learn how to manage and securely operationalize machine learning models at scale.

Explore how the AutoML nodes allow you to train classifiers by utilizing built-in feature transformations and optional automated hyperparameter tuning with our out-of-the box, and fully customizable gridsearch. AutoML models created using the Python-based engines of SmartWorks Analytics can be registered, versioned, and served through integrations with MLflow and Seldon Core. Empower everyone to make augmented, data-driven decisions. See how with SmartWorks Analytics.

Experience how Altair® SmartWorks™ gives you everything you need to quickly build scalable, secure web, mobile, and edge applications and then iterate fast to find product-market fit. This presentation, by Pérez Bello, Altair's Product Manager for SmartWorks originally aired at Future.AI in June 2021, and is a little over 11 minutes long.

As the pace of innovation accelerates, Altair is driving the future of smart, connected everything through the convergence of simulation, HPC, and AI solutions. Join Founder, Chairman, and Chief Executive Officer James Scapa to explore what he’s learned over more than 35 years assembling the right team and technologies to deliver this convergence and why it’s the key to unlocking your data potential and accelerating your digital transformation. This keynote presentation aired at Future.AI in June 2021, and is a little over 18 minutes long. Explore how to operationalize analytics and AI with secure, governed, and scalable strategies. View all Future.AI 2021 Presentations

Altair enables organizations worldwide to compete more effectively by operationalizing data analytics and AI with secure, governed, and scalable strategies. We deliver world-class, self-service analytics solutions for data preparation, predictive modeling, stream processing, visualization and more. With a no-code, cloud-ready interface, organizations can harness the full power of analytics and AI throughout its complete data lifecycle, driving next-level business results. Request a demo today.