SoftwareReviews Emotional Footprint Awards evaluate and rank products based on emotional
response ratings from IT and business professionals. Using our Emotional Footprint methodology,
we aggregate emotional footprint scores across 26 dimensions of the vendor-client relationship
and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
Emotional Footprint Awards are proudly founded in 100% user review data and are free of
traditional “magical” components such as market presence and analyst opinion, which are
opaque in nature and may be influenced by vendor pressure, financial or otherwise.
Read The In-Depth Report
See how each vendor stacks up across each of the 26 dimensions
and our thorough evaluation of vendor capabilities, product features, and overall satisfaction.
Emotional Footprint is scored using our “Net Emotional Footprint” Index. This index tracks responses
across 26 dimensions of emotional footprint that span 5 categories: Purchasing, Service Experience,
Product Impact, Vendor Strategy, and Conflict Resolution. Then, the following calculation is done
across this index:
% of Positive Reviews - % of Negative Reviews
For clarity, the total percentage of positive, neutral, and negative ratings is shown for each vendor as well.
The Databricks Lakehouse Platform combines the best elements of data lakes and data warehouses to deliver the reliability, strong governance and performance of data warehouses with the openness, flexibility and machine learning support of data lakes.
At KNIME, we build software to create and productionize data science using one easy and intuitive environment, enabling every stakeholder in the data science process to focus on what they do best. One enterprise-grade software platform, two complementary tools. Open source KNIME Analytics Platform for creating data science and commercial KNIME Server for productionizing data science.
Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.
The DataRobot Enterprise AI platform includes two independent but fully integrable machine learning model building products, and each can be deployed in multiple ways to match your business needs and IT requirements. All configurations feature a constantly expanding set of diverse, best-in-class algorithms from R, Python, H2O, Spark, and other sources, giving you the best set of tools for your machine learning and AI projects.
Alteryx provides a single workflow for data blending, analytics, and reporting. This workflow allows the seamless blending of internal, third party and cloud-based data, and simple analysis using 60+ prebuilt tools for spatial and predictive analytics.
Amazon Machine Learning is an Amazon Web Services product that allows a developer to discover patterns in end-user data through algorithms, construct mathematical models based on these patterns and then create and implement predictive applications.
Altair Data Analytics enables organizations worldwide to compete more effectively by operationalizing data analytics and AI with secure, governed, and scalable strategies. We deliver world-class, self-service analytics solutions for data preparation, predictive modeling, stream processing, visualization and more. Our solutions are designed for many different skill sets: from data scientists and engineers to MLOps specialists to business analysts to executives. With a no-code, cloud-ready interface, organizations can harness the full power of analytics and AI throughout its complete data lifecycle, driving next-level business results.
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