1. Driving Digital Transformation
Data holds the key to business insights that drive digital transformation initiatives in enterprises everywhere, helping business leaders to make the right decisions at the right time.
2. Focusing on Business Value
TIM’s approach to time-series modeling allows users to focus on the business insights that are contained in their data, while conveniently automating the handling of technical complexities under the hood.
3. Going Beyond Experimentation
Unlike the many machine learning projects that never get out of the expensive experimentation stage, TIM’s highly automated model-building capabilities ensure fast and scalable insights.
4. Getting Business Value through Augmented Analytics
TIM reduces the need for valuable resources (expertise, time, and money) and helps users leverage the insights hidden in their data to deliver real business value.
5. Approaching Time-Series ML in a New Way with InstantML
The TIM Engine creates models in a single step — from feature engineering to model building and deployment –, reducing the time needed for model building, as well as the engineering effort and mathematical expertise required.
6. Getting Results Fast
InstantML delivers results within seconds or, at most, a few minutes with one-step model creation, while reducing the need for engineering support.
7. Automating the Model-Building Process
TIM automates the feature engineering process, analyzing the historical input data and determining which features are relevant given the use case, without the need for dedicated expertise. After the relevant features are determined, TIM builds an explainable model using these features and provides users with the desired forecast or anomaly detection.
8. Generating Accurate Models
TIM’s thorough automation allows the engine to create models with equivalent or better accuracy than handcrafted models in a matter of minutes.
9. Explaining Model Insights
TIM generates transparent, human-readable models that provide users with comprehensive insights into the models created and helps them measure the impact of predictors and features on target values — automatically and instantly.
10. Integrating in Your Existing Landscape Easily
TIM can be accessed across a broad ecosystem of tools and platforms including public clouds, analytics and business intelligence (BI) platforms, data integration platforms, ML platforms, and Internet of Things (IoT) devices. This makes it easier to leverage TIM’s predictive analytics capabilities, because they’re available in applications and platforms that are already familiar to your users.
Based on: Predictive Analytics for Time Series with InstantML, by L. Miller and Tangent Works (2021).