Leaders accurately predict outcomes ― and apply prescriptive analytics to optimize how they take action. Success requires scalably tapping into Big Data sources using in-database analytics. It means effectively integrating predictive analytics and data mining into the full analytics lifecycle — sourcing, blending, visualization. And it requires empowering data workers from data analysts to data scientists with a code-free and code-friendly environment so that everyone, regardless of skillset, can effortlessly enrich their business function with advanced analytics.
Traditional advanced analytics tools require extracting data from the database — adding time and cost while limiting scalability. Alteryx in-database blending and analytics maximizes the power of Amazon Redshift, Oracle, Microsoft SQL Server, Cloudera Impala, Spark, and Teradata by applying formulas, filters, and joins, and performing advanced analytics to the data ― in place. It’s the essential ingredient to scale Big Data analytics.
Utilizing regression models, predictive models, and other advanced analytics techniques often requires skilled data scientists. With R and Python integration, and 40+ pre-built tools and macros for data investigation, predictive modeling, grouping, and time-series analysis, Alteryx enables data analysts and data scientists alike to impact future outcomes across their organizations.
Integrating, blending, and applying the latest machine learning algorithms to discover patterns in data is often an iterative, labor-intensive process. Alteryx provides the necessary advanced analytics tools to perform data mining techniques or leverage existing models through integration with R and Python, or full read/write of IBM SPSS and SAS files, providing flexibility through the analytics lifecycle, from data sourcing, blending, and enrichment to visualization.
Answering the question “what should we do?” often requires complex, error-prone spreadsheet models or manual coding. Alteryx brings optimization and simulation capabilities directly into a drag-and-drop workflow environment that provides consistency and transparency during the modeling process. Using a range of different mathematical models, support for different solvers, and built-in Monte Carlo simulation capabilities, making decisions with advanced analytics has never been easier.