Advanced Analytics and Data Science

• Requirement: Provision of Open-Source analytical frameworks or tools that are provided out of the box as part of the Data platform (e.g. machine learning).

• BDB Response: BDB Data Science Workbench with integrated Algorithms from R, Spark ML, Python, Keras + TensorFlow to create workflows and get business insights from different predictive models. It is a drag & drop based module through which Predictive Models can be used to envision the future outcomes of business processes based on past data. Custom Algorithms in R, Spark ML (Scala), Python can be designed. Sentiment Analytics, Image and Video analytics can also be performed using Deep Learning Workbench.

• Requirement: Ability to create analytical models, perform data mining, and apply statistical methods on data to generate predictive insights.

• BDB Response: Yes, BDB Platform has inbuilt DS Lab & Data Science Workbench with the advanced AI/ML capabilities to generate predictive insights in a Data.

• Requirement: Provision of a Sand Box environment to run analytical models which is scalable based on analytical workloads.

• BDB Response: Yes, the Data Center module of the BDB Platform has the Data Sandbox option for running/experimenting models.

• Requirement: Support for advanced analysis and modeling, leveraging optimized resources management to limit the tool needs while enabling computational heavy consumption for advanced tasks.

• BDB Response: Yes, the DS Lab module under the BDB Platform provides advanced analysis and modelling options to the data scientists for allocating the resources to run the model with ideal timeout option to release the resources for cost optimization. It also provides GPU support.

• Requirement: Monitoring and providing a layer of governance to guarantee the continue quality of the analytical models.

• BDB Response: Yes, BDB Data Science Lab enables the data scientists monitor quality and accuracy of the analytical models.

• Requirement: Capabilities in Deep Learning, with less dependencies on external libraries and hardware (e.g., GPU)

• BDB Response: Yes, BDB DS Lab has Deep Learning capabilities with option to configure additional libraries and hardware (GPU).

• Requirement: Capabilities to support NLP & Computer Vision.

• BDB Response: Yes, BDB DS Lab and Data Science Workbench supports NLP and Computer vision.

• Requirement: Enables connection with other external systems and components

• BDB Response: Yes, BDB Platform supports Model as an API and Pipeline consumption.

• Requirement: Combine technical capabilities and intuitive representations for the user to easily read and interpret the different diagnostics, explaining how models are performing.

• BDB Response: BDB DS Lab provides technical capabilities and intuitive representations for the user to easily read and interpret the different diagnostics, explaining how models are performing.

• Requirement: Support of advanced modelling capabilities by enabling the Deep Learning Architecture.

• BDB Response: Yes, BDB Platform provides support for the advanced modelling capabilities, enabling the Deep Learning architecture and provision for high level of customization.

• Requirement: Has a significant community using, supporting and documenting the framework.

• BDB Response: BDB Platform has a significant community that uses, supports, and documents about the various features of the product.