Solutions Review Names 4 Data Science and Machine Learning Vendors to Watch, 2020

Solutions Review’s Data Science and Machine Learning Vendors to Watch is an annual listing of solution providers we believe are worth monitoring. Companies are commonly included if they demonstrate a product roadmap aligning with our meta-analysis of the marketplace. Other criteria include recent and significant funding, talent acquisition, a disruptive or innovative new technology or product, or inclusion in a major analyst publication.

Data science and predictive analytics is one of the fastest-growing industries in the world. The field touts a burgeoning citizen data and enterprise software market mature with product options for an array of personas and use cases. AI and machine learning are major enablers here, both in terms of complexity and quality of output.  Complexity of analysis and automation are key buying drivers based on our meta-analysis. The amount of innovation happening in the development community will continue to vastly outpace mainstream adoption for at least several more years.

These data science and machine learning Vendors to Watch have met at least two of our five points of inclusion and represent to some degree the evolution of the marketplace. It’s in that spirit we turn our attention to the immediate future. Providers are listed in alphabetical order. Provider names and logos are linked so you can learn more.

Aible

Aible is an intuitive AutoML tool that enables users to create high-quality custom AI models focused on maximizing business impact. The solution requires no training or consulting, and optimizes for the net business impact of the AI. Aible conforms to regulated industries that require auditable AI, and recommends and enforces your AI training budget. Automated capabilities include data cleansing, feature creation, model training, data storing, model deployment, and quantifying impact.

Big Squid

Big Squid offers an automated machine learning platform called Kraken. The product features two-way connections to an organization’s existing data platforms. Kraken’s machine learning models help to uncover data quality issues before prediction. Kraken insights generate all hidden correlations in your data, including the weight that each metric has on the end outcome. An ML-driven scenario planning feature lets users see outcomes from taking different actions and plan for likely unknowns.

dotData

dotData offers an enterprise data science automation platform. The product can be piloted by both advanced and citizen data scientists. dotData can use flat files as well as relational data sets, and automatically discovers the table relationships and prepares data for feature engineering. Users can also generate automatic features and train models automatically via python ML algorithms. The API-based platform means you can validate model accuracy and retain models on the fly as well.

OmniSci

OmniSci is an analytics platform originating from research at MIT. The product allows users to interactively query and visualize data science workflows over billions of records. It features an open-source analytics database called OmniSciDB, as well a server-side engine for rendering pointmap, scatterplot, and polygon visualizations. A web-based visualization interface called Immerse provides standard visualizations as well as complex ones like geo-point maps and choropleths. Dashboards automatically cross-filter when interacting with data.