Disaster Recovery (DR) isn’t just “take a backup.” At MPP scale, you need a repeatable end-to-end flow with minimal coordination and downtime. This post walks through the DBA Operations Kickstarter framework that wraps gpbackup, gpbackup_manager, and gprestore into a fully automated DR pipeline

Self-service BI works when the data foundation removes friction for business users. Our reusable dimensional framework gives you trusted definitions, “as-was” and “as-is” choices, foolproof joins, and upstream data quality checks, so teams can explore confidently without hand-coding SQL or exporting to Excel (or god help us all MS Access).

Partitioning is a cornerstone of scalable analytics in Greenplum Database. The hardest part of partitioning isn’t design, it’s keeping partitions current. The kickstarter Partition Maintenance toolset is a set of Bash/Python utilities that operationalizes this lifecycle for Greenplum. This post will dive into this set of tools.

This blog summarizes a demonstration delivered to a customer interested in understanding how Greenplum can be used for machine learning, without exporting data to external systems. The objective was to showcase how churn modeling can be prototyped and iterated entirely within Greenplum using the gpmlbot utility, which automates feature preparation, model training, and evaluation.

Automating Agile Data Onboarding with Greenplum Sailfish

We understand the challenges of provisioning and operationalizing a Greenplum or Cloudberry data warehouse environment. Whether you’re deploying on physical infrastructure, virtual platforms, or the cloud, setting up a high-performance MPP database requires precision, expertise, and automation.

The DBA Operations Kickstarter is a comprehensive toolkit designed by Mugnano Data Consulting to automate and operationalize best-practice DBA workflows for Greenplum and Cloudberry environments. Whether you're onboarding a new system or stabilizing an existing one, this solution delivers an enterprise-grade operational foundation in hours, not months.

Dive deeper into how we leverage the extensibility features of the DbSchema Data Modeling Tool. Specifically, we’ll show how to design a dimensional model and generate DDL that directly integrates with Mugnano Data Consulting’s dimension utility functions