Data Science & Analytics Services


Data Engineering | Intelligaia

Data Engineering

  • Apache Airflow
  • Apache Spark
  • Google BigQuery
  • Hadoop/Hive/HDFS
Machine Learning | Intelligaia

Machine Learning

  • PyTorch
  • Dataiku
  • AWS SageMaker
  • Azure ML Studio
  • TensorFlow
Business Intelligence | Intelligaia

Business Intelligence

  • Tableau
  • Power BI
  • AWS Quicksight
  • Microstrategy
  • Google Data Studio


  • Data Warehousing & Data Lake: Building Data lakes, Data Warehouse and Data Lakehouse on AWS (Amazon Web Services) and GCP (Google Cloud Platform).
  • Data Wrangling: This involves processing the data in various formats, analyzes and get them to be used with another set of data and bringing them together into valuable insights.
  • Data Engineering: Building ETL & ELT pipelines from various data sources and building data workflows.
  • Data Analytics: Helping clients with descriptive, predictive and prescriptive data analysis and helping them to identify root cause.
  • Machine Learning: Building efficient ML models for predictive analysis.
  • Cloud & Solution Architecture: Building end-to-end solutions on AWS (Amazon Web Services) and Microsoft Azure.
  • Reporting and Dashboard building: Building OLAP reporting and OLTP reporting on Power BI, Tableau and SSRS (SQL Server Reporting Services).

Achievements & Milestones/ Deployments

  • Building an Enterprise data lakehouse on AWS (Amazon Web Services) for an SME client.
  • Data Visualisation for Enterprises.
  • Data Engineering on SAP HANA and setting up reporting architecture on Power BI for Business Insights for an Enterprise.
  • Data Analytics for Enterprises.
  • Worked on Data Warehousing for Business Insights and wrote multiple Stored Procedures.
  • Building Reporting System for Startups with applying ETL processes on Metabase.
  • Data warehouse, Business Intelligence and Data Mining project for an Enterprise.
  • Consulting for Enterprise to build MLOps and Data Engineering Platform.