Altair offers a comprehensive suite of data visualization software suitable for enterprise deployment. Business users, engineers, and analysts can connect to virtually any data source and build data monitoring, analysis, and reporting applications without writing a single line of code.
Altair offers a range of enterprise-class data visualization solutions and products that can be deployed in the cloud (public or private) or on-premises. Deploy our software quickly — in days, not months — and invite new users to begin building their own customized dashboards and streaming analytics applications within a few hours.
Our stream processing engine connects directly to real-time streaming and historic time series data sources, including MQTT, Kafka, Solace, and many others. Users can build event processing applications that combine streaming data with historic data, calculate performance metrics using a wide variety of statistical and mathematical functions, aggregate, conflate, and compare data sets, and automatically highlight anomalies against user-defined thresholds.
Use Altair® Panopticon™, data visualization software to extract real value from your data. Spot outliers, anomalies, trends, and clusters in seconds. Altair’s visual analytics tools are optimized to handle time-critical data, including data that may be changing with extreme rapidity. Filtering tools enable users to zoom in and out on the timeline, remove false positives from the screen, and focus on exceptions. Users can solve difficult problems quickly, understand complex relationships in seconds, and identify issues requiring further investigation with just a few clicks.
Protecting consumers and enterprises involved in online transactions is just one example of how machine learning (ML) influences our daily lives. In fact, the list of use cases is already long, diverse – and growing fast. The reason is clear – ML is a game-changing tool that enables organizations to make better decisions faster. What’s more, ML is highly effective at balancing conflicting objectives.
Given the breadth and depth of potential use cases, one thing is clear – more and more people will find themselves working in environments where ML plays a critical role. And thanks to the emergence of low-code and no-code software, ML is no longer the exclusive preserve of programmers, data scientists, and people who paid attention in math class. More of us can – and will – be involved in developing and deploying practical ML solutions.
This eGuide will help you understand the key concepts behind ML, some common applications, and how ML becoming more useful to people at all levels of the modern organization.