The best predictive analytics software enables organizations to map out future outcomes. Where traditional business intelligence tools help users analyze historical data to improve their decision-making, predictive analytics solutions allows for the creation of predictive models, or simulations, of what future conditions might look like. Predictive models are especially useful in environments where real-time analysis may mean the difference between success and failure.
The marketplace for predictive analytics software is relatively mature, and features providers that offer legacy BI and analytics software, as well as technology-forward vendors focused solely on data science and machine learning. Selecting the best predictive analytics software can be a daunting task, and we’re here to help. That’s why our editors have compiled this list of the 16 best predictive analytics software for 2019 and beyond.
For more you can consult our vendor comparison matrix.
Altair Knowledge Works (formerly Datawatch) offers its advanced and predictive analytics tools via three distinct products. Altair Knowledge Seeker provides data mining, as well as prescriptive and predictive analytics and decision trees. Altair Knowledge Studio includes advanced data modeling, scorecard development, and linear regression. Altair Knowledge Studio for Apache Spark enables users to better manage and create analytic workflows.
Anaconda is an open source Python and R data science platform. The tool enables you to perform data science and machine learning on Linux, Windows, and Mac OS. The product allows users to download more than 1,500 Python and R data science packages, manage libraries, dependencies, and environments, and analyze data with Dask, NumPy, pandas, and Numba. You can then visualize results generated in Anaconda with Matplotlib, Bokeh, Datashader, and Holoviews.
Alteryx Analytics allows users to organize, clean, and analyze data in a repeatable workflow. Business analysts find this tool particularly useful for connecting to and cleansing data from data warehouses, cloud applications, spreadsheets and other sources. The platform features tools to run a variety of analytic jobs (predictive, statistical, spatial) inside a single interface. Alteryx offers an expansive platform with many noteworthy analytic features, and their foray into data science tools figures to be a boon to citizen data scientists.
Databricks offers a unified analytics platform that allows users to prepare and clean data at scale and continuously train and deploy machine learning models for AI applications. The product handles all analytic deployments, ranging from ETL to models training and deployment. It is also available as a fully managed service on Microsoft Azure and Amazon Web Services. Reference customers rank Databricks highly for its end-to-end analytics lifecycle and support and accessibility for a variety of data science use cases.
Dataiku offers an advanced analytics solution that allows organizations to create their own data tools. The company’s flagship product features a team-based user interface for both data analysts and data scientists. Dataiku’s unified framework for development and deployment provides immediate access to all the features needed to design data tools from scratch. Users can then apply machine learning and data science techniques to build and deploy predictive data flows.
DataRobot offers an automated machine learning platform for data scientists of all skill levels to build and deploy accurate machine learning models. The tool automates the entire modeling lifecycle, enabling users to build predictive models. DataRobot searches through millions of combinations of algorithms, data pre-processing steps, transformations, features, and tuning parameters to spit out the best model for your data.
Domino Data Lab is an enterprise data science platform that allows data scientists to build and run predictive models. Its product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides users access to a Data Science Workbench that provides open source and commercial tools for batch experiments, as well as Model Delivery so they can publish APIs and web apps or schedule reports.
FICO Predictive Analytics enable users to create the best predictive models for their use case, whether an organization has an in-house analytic team or is new to the process. FICO’s suite of Decision Management products provides empirically derived custom models tailored specifically to proprietary product portfolios and customer bases, as well as pooled data and expert models.
H2O.ai offers a range of AI and data science platforms. Its H2O platform is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O supports widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O has also developed AutoML functionality that automatically runs through all the algorithms to produce a leaderboard of the best models.
IBM has made real strides to modernize its analytic offerings, and with great success. Cognos remains one of the most widely adopted BI platforms in the enterprise, and Watson Analytics is on the cutting edge of AI-influenced tools. IBM’s BI software can be deployed both on-prem or as a hosted solution via the IBM Cloud. The company’s complete analytics portfolio also includes its SPSS Predictive Analytics, IBM Data Science Experience, and IBM Planning Analytics tools.
KNIME offers an open-source analytics platform for intuitive, integrative data science. It also licenses KNIME Server, a tool for productionalizing data science by offering functionality for collaboration, automation, deployment and management. KNIME features more than 1500 modules, hundreds of ready-to-run examples, and a wide set of advanced algorithms.
MathWorks MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, tested, and fully documented. MATLAB apps let you see how different algorithms work with your data as well.
RapidMiner offers a unified platform for data science teams that includes data preparation, machine learning and predictive model deployment. The product touts a community of more than a quarter-million data science experts, as well as a marketplace that keeps pace with evolving trends. RapidMiner’s 60+ connectors provide access to any type of data, and users can run workflows in-memory or in-Hadoop.
SAP Predictive Analytics is an on-prem product that enables users to automate the entire predictive modeling process. The product features capabilities for embedding predictive analytics into line-of-business applications and business processes as well. It includes full connectivity to big data and third-party data sources, native integration with the SAP ecosystem, and link and network analysis features.
SAS Visual Analytics is available on-prem or in the cloud. Visual Analytics allows users to visually explore data to automatically highlight key relationships, outliers, and clusters. Users can also take advantage of advanced visualizations and guided analysis through autocharting. SAS has made its name as a result of advanced analytics, as the tool can ingest data from diverse data sources and handle complex models.
TIBCO’s product capabilities are expansive, and range from data integration and API management to visual analytics, reporting, and data science. The company’s BI and analytics portfolio comes in two main iterations: TIBCO Spotfire and TIBCO Jaspersoft. TIBCO Spotfire is the company’s more modern platform. It features interactive visualization, data preparation, enterprise-class governance, and advanced analytic capabilities.
Latest posts by Timothy King (see all)
- Outlier Nabs New Funding to Automate Business Analysis - January 22, 2020
- Forecast: 2020 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms - January 16, 2020
- Solutions Review Releases 2020 Buyer’s Guide for Analytics and BI Platforms - January 14, 2020