knowledge-studio

Analyze Shapley Values with Altair® Knowledge Studio®

Knowledge Studio supports analysis of Shapley values, a solution concept from the world of cooperative game theory. Data scientists can use Shapley values to explain individual predictions of black box machine learning models, including random forest and boosting models. This video demonstrates how to use Knowledge Studio’s SHAP (Shapley Additive exPlanations) node.

Getting Started

Predictive Models for Connected Products

Digital technology has changed the landscape of manufacturing and product creation: Internet of Things (IoT), artificial intelligence (AI), and data analytics are connecting organizations, generating data, driving more intelligent operations, and unlocking potential like never before. New skills are needed in the world of connected products and the success of innovation will depend on companies’ digital capabilities. This is why the investments geared toward adoption of digital technologies, products, and services that allow companies to thrive in the fast-evolving economic environment is growing. This white paper outlines the steps necessary to implement machine learning predictive models for connected products using Altair Data Analytics solutions.

White Papers

Build Autoregressive Integrated Moving Average (ARIMA) Machine Learning Models in Altair® Knowledge Studio®

Knowledge Studio supports Autoregressive Integrated Moving Average (ARIMA) models, a powerful way to make accurate predictions based on time series data. You can add ARIMA models to your AI workflows with a fully menu-driven user interface. The software’s Auto ARIMA functions automatically estimate values for ARIMA parameters using a grid search or step-wise algorithm. ARIMA is a simple yet powerful method for making time series forecasts, often incorporating seasonal and other types of semi-regular variations. For example, you can use ARIMA models to forecast electricity and raw materials utilization in a factory, output volumes in an oil refinery, fuel consumption for truck fleet, rail, and seaborne shipping companies, patient churn and intake volumes in hospitals, and key financial indicators for any type of business.

Use Cases

Altair Data Analytics for Banking, Financial Services & Insurance

Altair works with over 3,000 banks & credit unions, buy & sell-side trading organizations, security exchanges and insurance companies. Delivering best of breed applications from automated data preparation, and predictive analytics, to real-time data visualization. We provide you with technical resources from trusted subject matter experts in the field who understand your business, making your user experience seamless in transition. Altair offers a unique licensing model with cost-effective options to gain the competitive advantage in your market.

Datasheets

Harnessing the Power of Big Data, AI and Simulation to Accelerate Product Innovation

In a world where everything is becoming more and more connected, Mabe, a leader in home appliances, is leveraging the convergence of big data, analytics and simulation to accelerate innovation. Martin Ortega, Senior Design Engineer at Mabe, explains how they are using Altair’s AI, data analytics and simulation solutions to uncover insights, create new business opportunities, and advance product development. Explore the Power of Altair Data Analytics and AI .

Customer Stories

Transparent AI and Machine Learning: Altair® Knowledge Studio®

Knowledge Studio delivers explainable artificial intelligence (AI) and automates machine learning tasks to enable people to make fully informed decisions based on massive amounts of data. The software displays all the details of a model’s configuration so it is easy to understand how it generates predictions. Analysts who may not be familiar with modeling or AI processes can quickly uncover insights to help solve complicated problems. Data scientists can fine tune model parameters and develop highly sophisticated models using a drag-and-drop interface with no coding required.

Technical Papers

Analytics for Heavy Equipment

Serba Dinamik is an engineering company specializing in operations and maintenance (O&M), engineering, procurement, construction and commissioning (EPCC), and IT solutions for energy exploration and production firms. Their team worked with Altair to develop a Smart Predictive Maintenance Data System (SPMDS) utilizing Knowledge Studio and Panopticon. Maintenance crews use Panopticon-powered dashboards built into SPMDS to monitor every sensor mounted on operating turbines in real time. AI models built with Knowledge Studio identify potential failures or issues that require engineering attention, and, based on that understanding, take turbines offline only when necessary.

Customer Stories

Data Analytics Assessment Service

Altair’s Data Analytics Assessment Service helps answer the tough questions: • What data do I have? • Can it be leveraged for analytics? • What other data do I need and how do I get it? • What ML technology can be used with my available data? • How do I get started?

Technical Papers

Altair Knowledge Studio™ Overview - Advanced Machine Learning and AI

Data scientists and business analysts use Altair to generate actionable insight from their data. Knowledge Studio is a market-leading easy to use machine learning and predictive analytics solution that rapidly visualizes data as it quickly generates explainable results - without requiring a single line of code. A recognized analytics leader, Knowledge Studio brings transparency and automation to machine learning with features such as AutoML and Explainable AI without restricting how models are configured and tuned, giving you control over model building.

Videos

Substitute Missing Values in Altair Knowledge Studio

Datasets often have missing values due to file corruption, failure to record data points, or other causes. Handling missing data values correctly is critical to developing accurate predictive models. Knowledge Studio makes it easy to identify datasets containing missing values and generate new substitute values based on a variety of substitution algorithms. This video walks you through a simple example of how the software’s Substitute Missing Values node works.

Getting Started

Data Modernization: From Gathering Dust to Gleaning Insight

As part of the Altair Data Analytics Spotlight Series, we discuss modernizing your organization's data management so that you can unlock the full value of analytics and AI. If you're interested in developing a trusted data architecture that is accessible, centralized, and strategically designed to enable scalability and smarter decision making, then this webinar is perfect for you. During this webinar, we discuss how you can: - Centralize the storage of your siloed data - Improve data integrity with data normalization platforms - Analyze all of your data for deeper predictive insights

Webinars

Rapid Digital Transformation with AI-ML applied to Consumer Packaged Goods

In this webinar, we share our experience on the typical challenges faced by a CPG organization in the data analytics, AI, and ML context. A deep understanding of these challenges is also the key to the solution directions with the right mix of talent, tools, and technologies.

Webinars

Detect Simpson’s Paradox with Altair® Knowledge Studio®

In simple terms, Simpson’s Paradox occurs when a trend appears in subgroups but disappears or is reversed when subgroups are combined into a single dataset. Knowledge Studio supports detection of this statistical phenomenon. In this video, you will see an example of how Simpson’s Paradox can manifest itself and how you can use Knowledge Studio to detect its presence automatically.

Use Cases

Working with Imbalanced Classes in Altair® Knowledge Studio®

Most machine learning algorithms assume there are equal numbers of examples for each class in the source data. Many datasets contain substantially different numbers of records for important classes — resulting in an imbalanced class problem. Failure to handle this properly results in models with poor predictive performance. Knowledge Studio has a node specifically built to handle imbalanced class issues. In this video, you will learn how to identify an imbalanced class problem and use the software’s Handle Class Imbalance node to correct it. Refer to the Imbalanced-Learn Documentation website to learn more about the challenges related to working with imbalanced classes

Use Cases

Using the Generalized Linear Model (GLM) Node in Altair® Knowledge Studio®

In the context of machine learning applications, GLM models allows the use of dependent variables that do not follow normal distributions. This video shows how easy it is to use Knowledge Studio’s GLM node to utilize this advanced statistical technique to build more accurate machine learning models.

Use Cases

Combining System Modeling & Data to Optimize Heavy Equipment Performance

Information silos present a major challenge to Heavy Equipment OEMs. Poor integration of simulation models across the product life cycle, limited reuse of models between programs, and a variation of modeling maturity across various engineering disciplines result in lack of traceability and ultimately hampers development efficiency and product performance. Using system modeling and asset-centric data analytics solutions help develop and orchestrate coherent models to increase decision-making confidence and speed.

Technical Papers

Gain Future Insight with Your Human Resources Data

Human resources (HR) is tasked with recruiting the best talent and keeping culture at the forefront while staying on top of payroll, performance, and many other responsibilities. What if you could save time getting these tasks done while your human capital is ahead of the curve to meet your organization’s business goals?

Datasheets

Harvesting Engineering Knowledge from Consumer Generated Data

In a world where everything is becoming more and more connected, Mabe, a leader in home appliances, is using product connectivity to fuel a digitization strategy that delivers consumers the best experience through their solutions and services. Learn how they are using big data, AI, and analytics to uncover insights, create new business opportunities, and inform product development. The presentation by Martin Ortega, Senior Design Engineer at Mabe, aired at Future.AI in June 2021, and is a little over 17 minutes long. Learn what it takes to build a smart product – and where to begin. Download our free eGuide. View all Future.AI 2021 Presentations

Future.AI 2021

Data-Driven Dynamic Design - How Should a Robust System Component Look?

Safety and reliability are paramount objectives of the aero-engine development work. Comprehensive dynamic simulation and testing ensure safe and reliable products. However, new design architectures with increasing demand for power density need to be developed in even shorter time scales. Robust structural dynamics are one key objective that needs to be addressed very early in the concept design. Today’s analysis tools need to make accurate dynamic predictions at the system level which takes a long time due to very large design iterations and robustness assessments. An approach to resolve this dilemma by combining Altair SimSolid with frequency-based coupling and data science thinking is presented. The presentation by Carsten Buchholz, Project Engineer for Hybrid Electric Flight Demonstrator at Rolls-Royce, aired at Future.AI in June 2021, and is almost 13 minutes long. Ready to see how your company can drive innovation with AI-powered design? Contact our solutions experts today. View all Future.AI 2021 Presentations

Future.AI 2021

How to Accurately Assess Your IT Spend As a Global Technology Company

One of the challenges for CIOs and CFOs in managing IT spend is to get accurate data that can help to optimize spend. At Altair, we understand the need and we want to be your partner every step of the way. Learn how we delivered a most comprehensive data analytics solution for the IT finance team at Aptiv that helped to reduce operational time and automate the process of calculating the global IT spend accurately for managerial reporting. The presentation by Ripan Barot, Director of Professional Services and Customer Support at Altair, aired at Future.AI in June 2021, and is over 22 minutes long. See how Altair's predictive analytics solutions support calculating accurate IT spend. Contact us. View all Future.AI 2021 Presentations

Future.AI 2021

Process Automation & Predictive Analytics for Mortgage Portfolios

Explore how mortgage lending, operations, and servicing groups leverage data analytics solutions to automate processes, apply predictive and prescriptive analytics, and monitor assets visually. Join us to see demonstrations on data extraction, content management, predicting credit defaults, and visual analytics. The presentation, by Senior Solutions Specialist Alyson Kelley, and Subject Matter Expert Joe Lovati from Altair, aired at Future.AI in June 2021, and is almost 44 minutes long. Ready to explore predictive analytics and process automation? Contact us! View all Future.AI 2021 Presentations

Future.AI 2021

Improve Patient Experience and Operational Efficiency with Monarch and Advanced Data Transformation Tools

With the increasing adoption of telehealth and retailers expanding into healthcare delivery, patient demands for access and convenience continue to grow. Many organizations still rely on spreadsheets for key reporting and data management functions, but the manual processes required to manage healthcare data using spreadsheets are cumbersome and prone to error. Turning data into insight quickly is no longer optional and healthcare providers must respond with more efficient data handling workflows. In this session, we will explain how healthcare organizations can optimize their operations, improve patient experience, and reduce their costs using Monarch and advanced data transformation software in conjunction with spreadsheets. The presentation by Solutions Specialist John Strazdins, and Director of Healthcare Vertical at Altair Paige Jankowski, aired at Future.AI in June 2021, and is over 28 minutes long. Explore Altair Data Analytics for Healthcare View all Future.AI 2021 Presentations

Future.AI 2021

The Future of AI in Retail

Data scientists and business analysts across the retail industry use Altair to generate actionable insight from their data. In this session, we will explore how easy-to-use machine learning and predictive analytics tools empower you to rapidly analyze data and quickly produce explainable results - without requiring a single line of code. The presentation by Solutions Specialist Jack Lynch, and Director of State, Local & Education Vertical at Altair Mark Burns, aired at Future.AI in June 2021, and is over 21 minutes long. View all Future.AI 2021 Presentations

Future.AI 2021

Maximize Mining Equipment Performance with Altair Multiphysics solutions

The Mining industry faces a lot of challenges and remains under high pressure to control costs, improve operational efficiency as well as meeting stricter environmental regulations. Innovation and the use of technology play a key role in addressing these and in shaping the future of mining. This webinar will explore how simulation and advanced technologies such as digital twins, machine learning and Internet of things (IoT) can help mines increase productivity, reduce costs, and improve safety. You will hear from industry leaders and technical experts on how Altair’s solutions can be used for efficient development and operation.

Webinars

Digital Twins : IoT in Mining

The Mining industry faces a lot of challenges and remains under high pressure to control costs, improve operational efficiency as well as meeting stricter environmental regulations. Innovation and the use of technology play a key role in addressing these and in shaping the future of mining. This webinar will explore how simulation and advanced technologies such as digital twins, machine learning and Internet of things (IoT) can help mines increase productivity, reduce costs, and improve safety. You will hear from industry leaders and technical experts on how Altair’s solutions can be used for efficient development and operation.

Webinars

Transfer chute design and optimization using bulk material simulation

The Mining industry faces a lot of challenges and remains under high pressure to control costs, improve operational efficiency as well as meeting stricter environmental regulations. Innovation and the use of technology play a key role in addressing these and in shaping the future of mining. This webinar will explore how simulation and advanced technologies such as digital twins, machine learning and Internet of things (IoT) can help mines increase productivity, reduce costs, and improve safety. You will hear from industry leaders and technical experts on how Altair’s solutions can be used for efficient development and operation.

Webinars

Optimizing heavy equipment product performance combining system modeling and data

Several OEMs currently face the challenge of information silos due to poor integration of models across the product life cycle. Furthermore, there is limited reuse of models between programs and the variation of modeling maturity across various Engineering disciplines results in lack of traceability. In this short presentation, we will look at solutions and workflows that leverages a systems model as a common language of communication while facilitating various types of real time dashboards and visualization to help understand and optimize the entire Mechatronic system performance.

Presented at the ATCx Heavy Equipment in May 2021.

Speaker: Keshav Sundaresh, Global Director – Smart Systems & Mechatronics, Altair

Duration: 20 minutes

Presentations

Increasing the Value of Your Data: Getting Started with Machine Learning

Discover the benefits and ease of adopting machine learning into your data strategy with Altair Knowledge Studio. This webinar is perfect for anyone getting up to speed on implementing and using ML/AI – regardless of skill level or industry. During this webinar, we covered the following: - Getting started with machine learning (ML) and artificial intelligence (AI) and best practices - Applying and automating no-code ML modelling - Understanding responsible, explainable AI (XAI) capabilities - Going from predictive to prescriptive analytics to make smarter business decisions

Webinars

Engineers will make AI work

Anthony Mc Loughlin VP Sales Data Analytics, EMEA presents how to empower engineering to make data & AI work.

ATCx Industrial Machinery 2021

The Value of Data Analytics in the Smart Factory

Marco Fliesser Technical Director Data Analytics EMEA presents "The Value of Data Analytics in the Smart Factory ".

ATCx Industrial Machinery 2021

The Deep Dive: Practical AI and Data Science for Engineering

Engineers in manufacturing industries can spend as much as 50% of their time acquiring and synthesizing the data required to perform their day-to-day roles. We are convinced that engineers skilled in the use of AI toolsets hold the key to reducing the barrier to successfully capitalize on datasets across a wide range of complex manufacturing problems - from product design and new development to ongoing maintenance. These skills not only enable rapid, data-driven decisions and significantly improve productivity, but also empower engineers to meet the rising demand for an AI-skilled workforce. Take the next step in unlocking immediate opportunities for your manufacturing operations. Watch our in-depth session, The Deep Dive: Practical AI and Data Science for Engineers.

Webinars

Monetize Your Data Analytics Performance Through Collaboration

How can we take a step back from our current processes and improve them with new Machine Learning tools, or just clever reporting? In this session, our in-house solutions expert Alyson Kelley discussed how to monetize your current processes by: - Understanding current trends in data analytics - Creating strategic alliances within your organization - Taking advantage of partnerships with current vendors

Presentations

Streamline Audit Processes with Self-Service Data Preparation

Auditors are under significant pressure to keep expenditures down whether they work for an external audit firm or are part of an internal audit team. Achieving cost-effective audits requires organizations to do more with less - while maintaining or increasing audit quality. To succeed auditors not only need the right expertise and process but also the right data analytics tools.

Use Cases

Accelerate Data-driven Smart Operations with Altair Manufacturing Analytics

Explore how Altair enables enterprises to leverage operational data throughout the complete data lifecycle - from shop floor to top floor - with self-service data analytics and machine learning solutions.

Product Overview Videos

Knowledge Studio Spotlight Series - Fraud Detection and Prevention: A Data-Driven Approach

Fraud impacts everyone—from individual consumers to large corporations. Traditional rules-based systems may have been effective in the past in identifying fraud, but they become ineffective and stale as fraudsters learn how to bypass those rules. It becomes even more challenging due to the large volumes of data that need to be processed and examined to detect fraud, in addition to the constantly changing tactics for committing fraud – those activities are usually hidden in large volumes of data. Recently developed machine learning techniques are increasingly effective in detecting fraud with the advances in data systems (e.g. big data, streaming data) and computational systems (e.g. high-performance computing, GPU). As a result, it is possible to identify fraudulent patterns of behavior in data that is constantly being captured from day-to-day activities. In addition, it is feasible to address the challenges associated with fraudsters changing their tactics.

Webinars

Powerhouse Data Prep: Altair Monarch for Excel Users

Spreadsheet applications are ubiquitous, flexible, and give users the power to develop complex macro and formula-driven applications. The downside, however, is that spreadsheets are prone to error, difficult to program, produce results that are easy to misinterpret, do not handle data from multiple disparate sources easily, and are extremely difficult to maintain and debug as their size increases. Monarch can vastly reduce mistakes, save time, and support the most complex requirements.

Use Cases

Data Science for Engineering

Data science and AI are game-changing technologies for engineering and manufacturing companies. To embrace the need of today and the future for self-service data science and analytics in manufacturing, we need more data engineers to make this all possible.
At Altair, we envision a future where engineers are well equipped to apply data science techniques to derive powerful predictive analysis that transforms the way they operate. There are a plethora of applications for data science in manufacturing - from product design, supply chain optimization, and fault prediction, and preventative maintenance to demand forecasting, and quality assurance. By bridging the gap between the data scientist and engineering roles, your organization can breakdown data silos and extract actionable insights to drive real business value.
The movement has just started. Watch our on-demand webinar to learn more.

Webinars

Monarch Spotlight Series - Data Automation for Mortgage Servicing

Mortgage Servicers using Black Knight face significant challenges around quickly and cost-effectively accessing lending and prepayment risk. Mortgage Servicers rely on the client and transactional data to evaluate pre-payment risk and execute on investor reporting, loss analysis, and servicing transfers. On platforms like Black Knight MSP, that data is either trapped in static reports or accessible through costly add-ons like BDE. The Altair Mortgage Suite serves as a complement to the mortgage servicing platform by transforming reports into tabular data, applying machine learning, and presenting the data in a visual, easy-to-interpret fashion. Come join our in-house expert with two decades of experience in mortgage servicing Joe Lovati to learn how the Altair Mortgage Suite can bring efficiency to your processes.

Webinars

Don’t Waste Time Manually Preparing Data in Spreadsheets

Stop wasting time repeating the same manual data preparation task in spreadsheets. Experience how Altair Monarch is the solution to fast, automated error-free data transformation.

Use Cases

Data Analytics, Manufacturing Operations, & Quality

The ever-changing worlds of manufacturing and data analytics are now converging—and this intersection will soon greatly influence process management and quality engineering. Yet at all levels, quality professionals are grappling with the what and how of integrating data analytics. Altair Data Analytics recently partnered with ASQ to bring you a forward-looking discussion on data analytics, featuring special guests Sony Pauly (Technical Director—Northeast) and Dr. Tom Zougas (VP Worldwide Data Analytics Services) from Altair.
Listen as they discuss the questions and definitions that matter:

  • What does “data analytics in quality and manufacturing” entail?
  • What is smart manufacturing, or Industry 4.0?
  • How will the shift from preventive to predictive impact quality professionals?
  • How does data analytics impact anomaly detection, root cause analysis, predictive maintenance, and warranty analytics?

Webinars

The Truth about the Analytics Maturity Journey: 2021 Edition

Analytics Maturity Models have been around for 15 years, used by analyst firms and businesses across industries globally. But confusion remains about where exactly organizations place themselves on the continuum. Chris Long, VP of Worldwide Data Analytics Solutions Specialists—who was part of the original team at SAS that came up with the Analytics Maturity Model idea—shared his valuable perspective on its many iterations, and its application in 2021 and beyond. Take an insider’s look at the questions that need to be asked to truly figure out where you stand: -What are the most common misconceptions regarding the Analytics Maturity Model? -How can you verify where you are on the model? -What are the actions that we’ve seen clients take to level up on the model?

Webinars

Build Predictive Models for Failure and Multi-class Failure

Machine learning technology leveraging historical and real-time data from sensors mounted to production equipment as well as PLCs, SCADA, and other sources can accurately flag potential failures of whole machines and/or critical components before they can cause downtime.

Datasheets

Use Machine Learning To Predict Remaining Useful Life

Machine learning (ML) and stream processing technology are powerful solutions for remaining useful life (RUL) analysis. Manufacturers can use the large amounts of data produced by sensors combined with human inspections of finished pieces to train ML algorithms. The ML tools can then proactively alert operators when a tool is approaching its end of life, allowing them to schedule the replacement for a convenient time. Stream processing algorithms can also process all the sensor data being generated by any number of production machines, make on-the-fly comparisons with historical data, and increase the accuracy of ML algorithms. This solutions flyer explains how smart selection and application of ML tools combined with the availability of clean, governed datasets help manufacturers optimize their maintenance and wear part replacement schedules.

Datasheets

Data-Driven Warranty Risk Profile Analysis

Most manufacturers must handle large numbers of warranty claims related to a variety of products and components. The volume of claims can easily run to millions per year for consumer goods manufacturers. Patterns within claims data may indicate emerging quality or design problems; therefore, identifying and prioritizing the issues requiring high priority responses is critical to improving quality and reducing the financial impact of claims. This solutions flyer how advanced data analytics tools enable teams to cleanse and organize data from any set of repositories and apply machine learning technology to identify emerging quality or design issues.

Datasheets

AutoML, Explainable AI, Custom Nodes + More in Altair Knowledge Studio

Discover the new capabilities of Knowledge Studio that were released in 2020 to keep the tool moving as fast as science evolves. 2020 has been a slow and complicated year for some industries but not for technology. Technology continues to evolve at a fast pace and so should the solutions that support. Knowledge Studio has added some amazing features in 2020 to keep up with the trends in Data Science. Watch our lively discussion on the following new features: -Explainable AI capabilities for black box models -Automated machine learning for analysts that are not data scientists -Model Stacking to combine learnings from many models -Custom node creation through coding to keep work within the tool -Other new capabilities

Webinars

Detect Anomalies in Manufacturing Equipment and Systems

Identifying unusual behaviors or patterns in machine components using sensor data can prevent small glitches from creating major operational problems.

Datasheets

Innovative Tools for the Next Generation Data Scientist

We’ll take you through Knowledge Studio which is a market-leading easy to use machine learning and predictive analytics solution that rapidly visualizes data as it quickly generates explainable results - without requiring a single line of code. Knowledge Studio is a perfect fit to help manage credit and fraud risk, marketing analytics, product lifecycle design, customer loyalty programs, and supply chains. From healthcare to financial services, telecommunications to product warranty claims, Knowledge Studio enables analytics teams to gain useful, actionable insight from their data. Techniques we’ll walk you through: Code Interactivity Auto ML Explainable AI Model Stacking Who should attend? This event is perfect for anyone working with and analysing complex data in their organisations.

Webinars

Implement Effective Manufacturing Process Analytics

By extracting real value from their data, manufacturers can make accurate predictions about component life, replacement requirements, energy efficiency, utilization, and other factors that have direct impacts on production capacity, throughput, quality, sales, customer acceptance, and overall efficiency.

Technical Papers