Data pipeline development (ETL/ELT), data warehouse and lakehouse architecture (Snowflake, Databricks, BigQuery, Redshift), Power BI and Tableau dashboard development, data quality management and observability, real-time streaming analytics (Kafka, Flink), dbt-based transformation frameworks, DataOps implementation with Airflow and Dagster orchestration, and self-service analytics enablement for business teams.

ETL transforms data before loading to the destination — suited for on-premises data warehouses where destination compute is expensive. ELT loads raw data to the destination first, then transforms using the warehouse’s elastic compute — preferred for cloud platforms (Snowflake, BigQuery, Redshift). Kernshell recommends ELT with dbt for modern cloud data stacks — it is […]

Power BI is preferred for Microsoft 365 organisations (Kernshell delivers CEO dashboards, operational reports, and self-service analytics for Jabil and Hitachi Energy). Tableau for organisations with existing Tableau investments. Looker for Google Cloud-native deployments. Embedded analytics using Apache Superset or Metabase for custom application dashboards where end users need analytics without a separate BI tool […]

Yes. Kernshell builds streaming data pipelines using Apache Kafka for event ingestion, Apache Flink or Spark Streaming for real-time processing, and cloud-native services (AWS Kinesis, Azure Event Hubs, Google Pub/Sub) for managed streaming. Use cases include real-time fraud detection, live operational dashboards, IoT sensor stream processing, and customer behaviour analytics feeding real-time personalisation engines.