Data Science

Our all-encompassing data science solutions enable businesses to get maximum results from their data analytics endeavors. From consulting, developing, and deployment to implementation — with our data science services, you can enhance your AI capabilities to achieve the highest return on your investment (ROI).

We design AI models that provide measurable results rather than building complicated solutions with unnecessary, costly, and redundant elements that do not deliver value to your business.

Expertly harness AI, ML, and Deep Learning technologies to get ahead

We are skilled at incorporating the latest Deep Learning, AI (Artificial Intelligence), and ML (Machine Learning) technologies to deliver systems that help you delve deeper into your data to draw insights that inform your business decisions.

Our Data Science Competencies

Our approach

Analysis

We assess your existing systems and workflows to determine which AI (Artificial Intelligence) and ML (Machine Learning) techniques can improve their performance to deliver better results.

Develop framework

We establish the architecture for collecting, streaming, processing, and enriching data to decipher insights quickly and precisely.

Deployment

Domain specialists implement (Artificial Intelligence), ML (Machine Learning), and Deep Learning solutions using reliable methodologies and monitoring the performance.

Augmentation

We provide strategic solutions that help enterprises scale, enhance and grow their existing (Artificial Intelligence), ML (Machine Learning), and Deep Learning architecture and capabilities.

Our end-to-end data science services

With 120+ projects completed successfully, we are proficient at building the capabilities and architecture that enterprises require to grow and thrive in this modern era of cloud computing.

  • Data ingestion from the use-case-specific data sources
  • Structure, organize, and model data through data preparation
  • Define the algorithms suitable for the specific solution being developed
  • Design relevant Machine Learning (ML) models
  • Run the algorithms multiple times
  • Rank and score items for building models
  • Monitoring and continuously training data models

Successful implementation of predictive technologies by PBI Analytics

Solution Implementation

Diagnose, determine and strategize

We assessed each element of the client’s predictive analytics solution’s infrastructure, technologies used, scalability challenges, and available budget.

Create solution blueprint

Based on the requirements, we developed data ingestion workflows for orchestrating data movement and transformations at scale.

POCs deployment

We produced and deployed POCs (Proof Of Concepts) to assess the improvement delivered in the predictive analytics solution.

Suitable solution implementation

We then implemented the relevant in-memory OLAP cubes building technology to analyze data in real-time, calculate predictions to create ad-hoc reports in real-time, and carry out root causes analysis to determine the right course of action for fixing and avoiding such events or issues in the future.

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