By: Oli Plaistowe, Head of Solutions at World Programming, UK
Forrester cites World Programming as a Challenger in its report, The Forrester Wave™: Multimodal Predictive Analytics and Machine Learning (PAML) Solutions, Q3 2018.
Leading independent research agency Forrester invited us to enter the Forrester Wave™ evaluation for PAML Platforms. We felt our product was finally up to the challenge of analyst scrutiny, with the introduction of our data science module.
Historically, our product offering has focused on the SAS language, helping organizations to reduce the cost of running their SAS language programs. We have consistently increased our market share from individual users through to global organizations in Financial Services, Telecoms and Retail.
More recently we embarked on a journey to integrate open source languages together with the SAS language into a single environment for working with data, using a powerful graphical user interface. We saw a demand for a multi-language analytics platform supporting a wide range of skill sets within data science. Our new set of features enables users to prepare, wrangle and explore data with a choice of visual or coding tools. Advanced users can leverage the predictive modeling, machine learning and reporting capability.
Whilst the data science feature-set we currently offer is limited in comparison to some of the established vendors in this market segment, our products are built on a solid analytics infrastructure that we have developed over the last 17 years, and which is trusted by some of the largest enterprises in the world. Whilst there are many players in the PAML segment, we are the only new entrants able to run industry-standard SAS language whilst incorporating emerging analytics technologies such as Python and R relied on by many of the other new entrants.
We have long been interested in the data science lifecycle including how companies manage their models from inception through deployment to monitoring and retraining. Global organizations ask us how they can reduce the time to take models from building and testing to operational deployment. Big Data and demand for large numbers of complex analytical projects has made DevOps (operational management of models in this context) a significant bottleneck. To address this, we have built a web-based model repository that data scientists can use to deposit models ready for deployment, without requiring expensive and error-prone recoding – a common gripe. The easy-to-use GUI makes model deposit and deployment effortless, and the repository provides centralized security management and deployment and governance of predictive models. This is the WPS Analytics Hub.
Would you like to discuss your requirements or arrange a demo?
Our goal is to offer the best unified data science platform available. “Best”, to us, means reliable, scalable, performant, flexible integration of technologies, easy-to-use, and competitively priced. As we continue to execute on our current five-year roadmap, we will be working closely with our customers to find innovative ways to drive value for them from their analytics processes. We will use the experience to help shape the future features of the WPS Analytics platform. Please get in touch with us if you would like to be a part of this process.
We are delighted with this recognition by Forrester and believe it to be validation that we are on course to become a leading player in data science.