Overcome Big Data Access Challenges with Knowledge Studio for Apache Spark™

In the second installment of this Data Science for Engineering series, we covered:

• Predictive modeling and evaluation techniques
• The Cross-Industry Standard Process for Data Mining (CRISP-DM) framework
• Spotlight on Altair customer stories - Ford Motor Company and Renishaw
• Technical demonstration of building machine learning models for predictive maintenance, testing, and quality analysis
• Live Q&A Session

We kick off the Data Science for Engineering series by covering the first step of data science methodology. During this 90-minute presentation and Q&A we discuss:

• The "why" of engineering-data science convergence holds the key to unlocking the full potential of data and AI in manufacturing​.
• The data science basics including the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework​.
• How Mabe, a leader in home appliances, is leveraging the convergence of big data, analytics, and simulation to accelerate product innovation​.
• How you can gather, combine, structure, and organize engineering data using a self-service data preparation solution​ with a technical demonstration of Monarch.

Is data a challenge or an asset for your HR department? Discover how to minimize the time spent on reporting while maximizing insights from your available data sources. The HR department’s monthly, weekly, and even daily reports have a wide range of complexity and importance. From the “no-fail” tasks of payroll reporting to the in-depth look at the overall health of an organization through talent acquisition and talent retention, the role of HR and the data it needs for the job are inseparable. Our analytics expert will reveal how you can: - Manage data from payroll systems - Track diversity hire information YoY - Assess the health of your organization - And more! Visit our HR Analytics page for additional resources

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

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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?

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?

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

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.

Post COVID-19 and as we navigate our new normal - banking and lending will undoubtedly be transformed. As the economic fallout spreads, financial firms are grappling with a major influx of relief requests from consumer and business customers. Our panelists discuss whether modern technology, advanced analytics, and a data-driven approach can hold the keys to ensuring banks and fintech leaders continue to scale despite this rapidly evolving credit crisis.

Featuring an enviable lineup including; Frederic de Sibert, Global Head of Investment Banking Services Strategists at Goldman Sachs, Paul Downes, COO at Autovista Group, Kerem Talih, General Manager/CFO at Doğuş Otomotiv and Dr. Mamdouh Refaat, Chief Data Scientist at Altair. This hour-long webinar is full of insight, guidance, and tips from global businesses that are at various stages of their Data & Analytics journeys.

Hear from a prestigious panel of experts including David Huguet, Data Lead at SNCF, plus Martijn van Baardwijk, CFO - Continental Europe at Inchcape plc.

Augmented Analytics is being touted as the next frontier in AI’s Evolution with Gartner defining it as “the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data”.

Marketers need to better understand changing preferences and shifting demand so they can personalize their interactions. Altair Data Analytics solutions help clients derive deeper, faster customer and prospect insights by blending and analyzing data across all channels, without any coding or IT dependencies.

Fraud mitigation requires technologies and business processes that are flexible in their construct, easily understood by all who are involved in fraud prevention, and are agile enough to adapt to new attacks without needing to be rebuilt from scratch.
Data from all business units and functional silos must be included to create a holistic view of the success of fraud operations. The insight found in classical auditing techniques and predictive machine learning models, combined with the expertise of fraud analysts can foster an evidenced-based methodology to quickly respond to new financial crimes.

This presentation is about making machine learning models and their decisions interpretable, and why it's important and valuable.

What is Predictive Modeling?  Why is it useful?  How do you leverage Predictive Modeling in a practical sense for your business?  Users will end this session with a better idea of how they might be able to apply predictive modeling to their own potential use cases. In this webinar, we explore, an introduction to Predictive Modeling, a practical help as to how business and analytics users can best leverage predictive modeling tools, ways to challenge and test predictive models to ensure confidence in performance, and best practice examples of how to deploy the results from predictive.

Machine learning techniques for CAE applications using Altair Data Analytics software.

A profound shift in the world economy means that businesses will rely more on analytics to predict a behavior down to a particular confidence interval. Loss of revenue streams and mitigating other risks highlights the importance of using data to drive decisions around strategies that are intended to maintain revenue, reduce costs, and navigate through other challenges.

Altair Data Analytics helps the Intelligence Community implement and streamline advanced interoperability through smart data preparation and predictive analytics, allowing security analysts to rapidly access, clean, and transform difficult data from disparate sources into a leverageable, shared asset for efficient reporting. During the 20-minute session presented at the recently-held Intelligence Analytics Virtual Summit, we discussed how to leverage data preparation and predictive analytics to automate repetitive, error-prone processes associated with accessing and reconciling data, eliminating manual work, and fostering smart decision-making across the board.

This video explores the many ways Altair Data Analytics software may be applied in financial services environments. Learn how to improve your skills in data preparation, machine learning, and data visualization.

Learn how you apply real-time data visualization and stream processing technology in financial services environments to identify profitable opportunities and avoid compliance risks.

Altair Data Analytics tools support data preparation, data prediction and data visualization. In this webinar, we introduce the machine learning capabilities of the Knowledge Studio product. The webinar contains: A brief introduction to the concept of Machine Learning A live demo solving a problem using Predictive Maintenance Methods for transforming the Machine Learning algorithms to actual profit

How do you define and minimize risk in uncertain times? The simple, transparent and easily explainable modeling technique of scorecarding can help to support credit decisions such as scoring new lending applications, changes in credit limits, over-limit approvals on transactions, etc. In today’s rapidly evolving world, a solution that allows for the refreshing and reusing of scorecard development workflows in minutes--without the need to write code—is crucial.