DMWay Analytics Engine Reviews

Easy to use. Best automation and scalability

Limited model flexibility and cost and support

The ease with which predictive models can be deployed in real-world applications is essential. Many predictive analytics engines facilitate model deployment, whether in a cloud-based environment or on-premises

A wide variety of interactive visualizations and customizable dashboards, having widgets, graphs and dashboards allowed me to better explore the data, identify trends and compare metrics in a more dynamic and intuitive way, the ability to filter and select dimensions from the visualizations without having to modify reports. I found it very practical for exploratory analysis

What I was least convinced about was some limitations in connections with external databases, especially with systems that are not relational, although it supports a wide range of data sources I had problems mapping collections within a MongoDB database and data extraction takes longer than expected this made it difficult for some projects to load large volumes for certain types of analysis

helps me solve are the arrangement of fragmented data in multiple sources and systems, and the difficulty in generating dynamic visualizations that allow new business perceptions. By having a single platform that allows information to be loaded from different sources, the process is greatly simplified. With data integration, I can spend less time cleaning and processing scattered information, which speeds up analysis. Having an extensive library of charts, dashboards, and reports has given me the ability to better explore data