Name: Navigating the Data and Analytics Maturity Curve: Strategies for Excellence
Start: 2024-05-29T15:13:00Z
End: 2024-05-29T15:13:18.000Z
Location: BrightTALK
Rating: 0

Altair is a global technology company that provides software and cloud solutions in the areas of data analytics, simulation, and high-performance computing (HPC). 

Altair Data Analytics enables people of all skill levels to access, generate, and use smart data to make insightful, informed decisions.

Our no-code data transformation, AI/ML, and data visualization tools reduce the complexities often encountered in data analytics. We eliminate the need for specialized programming knowledge and democratize the analytics process. As a result, people across the business can leverage the value of insightful analytics. 

Visit www.altair.com/data-analytics to learn more!

Effective predictive maintenance systems use machine learning algorithms to process real-time sensor data on temperature, pressure, torque, vibration, and other key parameters to determine when failures are likely to occur. Watch this video to learn how Altair tools can help determine the variables with the most predictive power, how to train predictive maintenance models with historical data, and how easy it is to deploy models into an operational workflow.

Use Machine Learning to Implement Effective Predictive Maintenance

Premium AEROTECH is responsible for the fuselage and its structures in the complexities of aircraft.  To ensure the absolute certainty of the safety of their products, Premium AEROTECH uses Synera software throughout their development stages, as shown in this engaging customer testimonial.

Please note this video is in German with English subtitles.

Voice of the customer - Premium Aerotec for Synera (formerly known as ELISE)

Developing vehicle design and technology for more than 50 years, EDAG prides itself on always looking ahead to the future of mobility in an automated world. Coupling this with the fascination of technology, EDAG uses Synera software to speed up their re-design process along during development.

Please note this video is in German with English subtitles.

Voice of the customer - EDAG for Synera (formerly known as ELISE)

The latest versions of Altair AI Studio and Altair AI Hub (formerly RapidMiner Studio and RapidMiner Hub) include interactive decision trees, improved integration capabilities, connectivity, and performance, and simplified our deployment options. Watch this short video to learn more about the improvements in this release.

Introduction to Altair AI Studio and Altair AI Hub 10.2

Altair RapidMiner: AI and Data Analytics Platform. In this video, take a look at how to use the zero-shot classification operator utilizing the genAI extension with a healthcare use case.

Altair RapidMiner: Generative AI Zero-Shot Classification Operator

Altair Graph Studio is the fastest, most advanced way to manage and integrate all your data, shattering the limits of technologies like data warehouses and data lakes. Graph Studio utilizes semantic technology to describe, blend, and harmonize data sources using common business meaning as well as context to make your data more understandable, often exposing additional connections you didn't even know were there, and enabling data and knowledge to be accessible to virtually everyone in your organization, from experienced data scientists and data engineers to business users. All of this can enable 360-degree customer views, fraud detection, research and development, and clinical trials.

Altair Graph Studio: Scalable, Knowledge Graph-driven Data Fabric Layer

In this presentation, we explore the rationale behind integrating data with Knowledge Graphs, outline their fundamental concepts, and demonstrate practical implementation using Altair Graph Studio. Join us to get an introduction to the transformative potential of this technology.

Presented as part of Altair ATCx AI for Engineers 2024 conference.

Integrating Data with Knowledge Graphs: Why, What, and How?

(PREVIOUSLY RECORDED)
Manufacturers are increasingly relying on data analytics to optimize operations, and for good reason. Manufacturing environments are data-rich. Data from sensors, machine logs, and production records can be used to extract valuable patterns and insights, which can help avoid downtime, reduce scrap, and improve sustainability. Implementing data analytics is an essential part of the digital transformation journey and more attainable than you may think.

Watch this webinar with ABI Research and Altair to:
 - Determine what factors to consider when evaluating manufacturing data analytics vendors 
 - Learn about Altair RapidMiner, ABI’s top-ranked data analytics and AI platform for manufacturing analytics 
 - Get inspired by real-life manufacturing use cases and successful deployments
 - See how to maximize the value of your data and compete well into the future.

Webinar: Unlocking Manufacturing's Data Potential with AI and Analytics

Welcome to this demonstration video of the Altair RapidMiner platform, our end-to-end AI solution for all users in your enterprise.
Altair RapidMiner is a platform in which data science, machine learning, AI and traditional data analytics converge.
There are close connections to Altair's other two platforms for simulation and high-performance computing. But today's demonstration will mainly focus on Altair RapidMiner.

Agenda:
- Planning and Design
- Data Preparation
- Data Exploration and Visualization
- Data Science Techniques and Machine Learning
- Generative AI
- Notebooks and IDEs
- Model Consumption
- Project Progress
- Key Take Aways

Altair RapidMiner Demonstration

Businesses across all sectors are facing significant challenges when it comes to modernizing their data analytics stack.

Terms like 'data transformation' and 'infrastructure optimization' are always used, but what does that mean? How do the people on the ground, like you, even begin to address how to approach the vast and nuanced projects related to modernization?

The most pressing question we hear from our customers is: How can we maintain investments made in legacy systems, like those created using SAS, and leverage modern platforms that offer new benefits and address issues like staff skills, open-source deployments, flexibility, and transition to the Cloud?

In this 30-minute webinar, our experts will discuss:

How to identify factors that impact reliability when looking at sizeable enterprise-wide modernization projects
Real-life successful deployments and why our phased approach works for large organizations
How you can leverage new Generative AI technologies safely and effectively
How our technologies can help you build your unique competitive advantage without having to throw away investments made in legacy structures and systems
How to accelerate your journey to the cloud

Clear Path to Modernization: Future-Proofing Your Data Analytics Infrastructure

With the emergence of ChatGPT we have reached another pivotal moment with AI. At the very least, it has unlocked a next-level fever of interest in AI and potentially the ability to disrupt whole industries. This has arguably most organizational leaders wondering, how might this impact my business. In this panel discussion, we will explore the potential impact on manufacturers.

Panelists:
Naresh R. Jasotani I AI/ML Innovations Lead-Automotives, US I Google Cloud
Dr. Ingo Mierswa I Senior Vice President, Product Development I Altair
Mark Do Couto I Senior Vice President, Data Analytics I Altair
Mahshid Shirani I Data Science Manager I Altair

Changing the Pace of Manufacturing Transformation through Generative AI & LLM

This video demonstrates how the Altair team utilized our solutions to identify characteristics that lead to a higher risk of flood and ways to help mitigate the displacement and loss of life due to these events.

We’ll show how we used the Altair RapidMiner platform to:

Get to insights faster by enabling domain and data experts to collaborate seamlessly
Leverage existing SAS language and Python code in a multi-language environment
Deliver flood risk warnings, ahead of time, to the right stakeholders with a real-time dashboard

Data preparation for income and expense shock

Visualize and validate credit risk models

Visualize and validate credit risk models : Episode 3

We understand safeguarding your portfolio from current economic shocks is your top priority. That means you require a throughout data-driven approach for credit-risk assessment. Then your credit-decision model should be the reflection of the same and needs to be continually fined tuned. Altair with Deep Credit Risk brings Credit Risk Trends and Analytics, a three-part webinar series on credit risk analytics with a focus on the pain points of developing models that reflect the driving economics.

In part one webinar, we understood the challenges in the credit risk industry. Build an understanding of the role of liquidity, equity, and many other key banking features. You learned to do feature engineering and efficient selection, for instance, the impact of income and expense shocks on loan repayments. You were able to pre-process credit information, import information, and merge data from various sources.

Now, with the right data, in this part-two webinar, you will learn to build credit risk models through machine learning techniques and understand the impact of the economic downturn on the model outcome. You will develop a good understanding of the pitfalls of machine learning and the merits relative to econometric regression techniques. You will be able to predict defaults, payoffs, loss rates, and exposures. You will be able to efficiently validate credit risk models. We will compare and interpret various validation strategies and learn how to build meaningful user interfaces, compare outputs for models in terms of stability, discrimination, and calibration and efficiently communicate outputs. This will give you the confidence to build credit models accurately as we cover deep domain knowledge on-

Key Discussion Points:
§ Non-Linearities of risk drivers
§ Impact on Illiquidity and Leverage
§ Machine Learning Models
§ Bias-Variance trade-off
§ Predictability and pain-points
§ Showcase of lender internal data

Credit Risk Modeling Using Machine Learning : Episode 2

Martha Bennett I VP, Principal Analyst, Forrester
In this presentation, Martha Bennett discusses:
•How leading firms are using data & analytics to reduce risk
•What impending and potential AI regulations mean for banks and insurers
•How a solid foundation of data and analytics is the key to agility and innovation

Be Future Fit With Data And Analytics

In this presentation, we explore the transformative journey of data and analytics maturity within organizations. Focusing on Analytium's strategic approach to developing a comprehensive business data strategy, we delve into methodologies that guide businesses from foundational reporting and dashboarding towards advanced analytics and AI-driven decision-making. By highlighting the progression through predictive, prescriptive, and cognitive analytics stages, we demonstrate how companies can unlock significant value and complexity management. Through real-world examples and best practices, we aim to equip attendees with the insights needed to navigate the data maturity curve effectively, ensuring their organizations are not just surviving but thriving in the data-driven era. Stay until the end of the presentation to receive an exclusive invite to our online assessment tool.

Navigating the Data and Analytics Maturity Curve: Strategies for Excellence

Data Analysis

Data Analytics

Data Best Practices

Business Analytics

Strategy

data-driven

Maturity Curve

Data Journey

Methodologies

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Business Intelligence and Analytics

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Navigating the Data and Analytics Maturity Curve: Strategies for Excellence

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