Few things in business are certain. The value of preemptively diagnosing and resolving an issue before costly failures occur is significant. Traditionally, developing and maintaining systems to help prepare for the unexpected have been cost-prohibitive except for the most mission critical or high-frequency business processes. No longer.
Anomaly detection (or outlier detection) identifies items in a dataset that do not fit with the others. Because they don’t require human input, these algorithms are a cost-effcient way to monitor for the unexpected. Simply add a dataset, and quickly identify the data that looks suspicious and warrants further investigation. And if you have or collect labels for known anomalies, the system can continuously adapt and improve.
Use nD to effciently identify issues in an ad hoc dataset or build a real-time monitoring center at scale. Improve algorithms to minimize false positives and create an accurate, effective detection system. With nD, you’ll be prepared for the unexpected.
Data is uniquely capable of telling a story about your business operations without predefined boundaries or assumptions. The recent wave of big, Internet of Things (IoT) and public data has created datasets unlike any you’ve seen before. The key is unlocking the value in time to act.
A category allows your domain experts to leverage smart data visualization to quickly slice and dice a dataset to gain insight, and ultimately to assign appropriate actions to a given situation. But what happens when there are no categories or the right categories have not been explicitly added? Clustering is the identification of inherently similar rows within a dataset, accelerating your journey to insight and action.
nD helps you quickly identify implicit categories and aggregate them into new explicit categories for discovery and decision-making. Use nD to uncover groups of transactions, events, people and things that can be leveraged to quantifiably improve your business outcomes.
The right data allows your team to estimate the probability of future events and thereby improve business outcomes. Once they find an anomaly, they can determine the probable root causes, and given past categorizations they can determine whether new transactions, events, people and things belong to a category in real time.
Classification models use past data to estimate these probabilities. Operationalizing this knowledge must account for the predicted likelihood of the event, as well as any penalties associated with getting it wrong. Not everyone is comfortable making decisions based on what is likely, and not every decision can be made without certainty. But those who embrace the uncertainty, where they can, will gain a significant competitive advantage.
nD empowers your team to efficiently build classification models, apply them to new data and use the insights to get a leg up on the competition. Whether conducting a one-off diagnosis or building a real-time diagnostics center at scale, nD is right for the job.
Hindsight is 20/20. In some cases, time sheds light on the relationships between factors and outcomes, and in others additional variables emerge that weren’t initially available. In either case, imagine if your business experts had the ability to explore the impact of their decisions before committing to them?
Modern nonlinear regression models are able to estimate downstream dependent variables based on upstream independent variable, through even the most complex business and physical processes. Arm your team to estimate business outcomes before and as they act.
The powerful, self-service nD web portal empowers your team members to build and deploy powerful regression models, and scale up to embed key models into your own real-time production applications.
What if you were able to predict the trajectory a dynamic process would take in the future, and plan your actions accordingly? Predicting outcomes – whether a few minutes, hours, days, weeks or months into the future – allows your team to make real-time decisions and sequence deliberate actions that will support your desired business results.
Predictive models use information from the past to understand dynamics in the system and forecast the future. Predicting the “when” of future values gives your team the opportunity to know exactly what path they are on and prepare, adjust and invest accordingly. Adding forecasts for markets, demand, costs and inventory makes operations and planning initiatives truly adaptive.
nD can withstand the volume, variety, velocity and veracity of big data. With nD, your team can create operational intelligence and adaptive planning applications, ensuring you’re always one step ahead.
Missteps, errors, anomalies. If your systems and operations are truly data-driven, these aren’t purely negative occurrences, but part of the cycle of improvement. Machine learning algorithms are adaptive in nature, continuously learning to improve accuracy. Results and options can be reevaluated in milliseconds, making machine learning a crucial and exceptionally effective tool to support decisions no matter how complex and high frequency the process.
Optimization systems leverage the full capabilities of anomaly detection, clustering, classification, estimation and prediction to robustly maximize your business objectives. You quantify your objectives, any operating constraints and the levers that can be manipulated; and the optimizer’s job is to determine a valid set of adjustments for your
current situation. You simply make the adjustments and repeat.
nD is the ultimate analytics platform to support a data-driven organization. nD offers an end-to-end environment to collaborate on visualization, analytic and machine learning applications; and build a rapid, iterative, and experiment-driven culture.