Solutions Review Names 5 Data Science and Machine Learning Vendors to Watch, 2021

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.

DataChat

DataChat offers a conversation-based data analytics companies which uses AI and natural language technology to conduct analytic functions. The product includes capabilities for exploratory analytics, predictive analysis, structured querying, free search querying, data wrangling, and visualization. Users can create sophisticated data science programs without code. Explainable AI and AutoML uncover patterns in data and report it in plain English. DataChat is offered as a fully-managed, containerized service in the cloud.

Explorium

Explorium offers an automated data science platform uses AI to automatically connect to data sources and distill the most impactful signals for a predictive question. Users can easily build and deploy models right from the platform, as well as connect to thousands of external data sources so customers can scale use cases. Explorium can be used in a number of different ways. The platform can be deployed as part of your data science pipeline or as a managed service.

Iguazio

Iguazio offers a data science platform that automates workflows. The product can ingest multi-model data like event-driven streaming, time series, NoSQL, SQL and files in real-time. Iguazio lets users explore and manipulate data online and offline, and the platform is powered by a real-time data layer that uses a variety of data science and analytics frameworks which come pre-installed. Users can train models continuously in a production-like environment that dynamically scales GPUs and managed machine learning frameworks as well.

Siren

Siren offers an investigative intelligence platform that uses a data model to drive the discovery of associated data. The product fuses previously-disconnected paradigms like business intelligence dashboards, link analysis, content search, and operational monitoring. Siren lets you connect to Elasticsearch, RDBMs, graph databases, and web services and touts more than 200 connectors. The user interface blends full-text search with support for misspellings, phonetics, relevance ranking, and highlighting. It also features Geo and Temporal analysis to allow multi-layer, interactive maps and time analysis.

Unsupervised

Unsupervised offers an augmented data science and machine learning tool that automatically finds patterns in data and presents them for review. The application analyzes the full complexity of enterprise data and identifies significant patterns that highlight the differences across subgroups of data. Unsupervised uses a number of machine learning techniques to identify patterns. Once it has discovered patterns in data, Unsupervised analyzes each subgroup to see how it performs against organizational KPIs.