Case
Studies

01
Approaches & Techniques

Best & Modern Practices

We help you with the best practices on Data, AI and Tech given your specific use-case.

Such as:

Apache Iceberg V3

Apache Iceberg™ v3 contains major new features (deletion vectors, row lineage, semi-structured data, geospatial types) and unifies the data layer across formats

DuckLake

DuckLake is an integrated data lake and catalog format

DuckLake delivers advanced data lake features without traditional lakehouse complexity by using Parquet files and your SQL database. It’s an open, standalone format from the DuckDB team.

Delta Lake

Delta Lake is an open-source storage framework that enables building a format agnostic Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, Hive, Snowflake, Google BigQuery, Athena, Redshift, Databricks, Azure Fabric and APIs for Scala, Java, Rust, and Python. With Delta Universal Format aka UniForm, you can read now Delta tables with Iceberg and Hudi clients.

Traditional Data Warehousing

A data warehouse is a centralized repository that stores large volumes of structured and sometimes semi-structured data from multiple sources. It is designed for querying, analysis, and reporting, enabling businesses to make data-driven decisions.

MCP Servers

Lightweight programs that each expose specific capabilities through the standardised Model Context Protocol. Local Data Sources: Your computer’s files, databases, and services that MCP servers can securely access.