Bragi is Cortex product that has grown out of a homegrown utility to make us more productive. We do lots of work with data. Seeker is all about the data - Bragi is the workhorse behind it and has allowed us to pull data in from over 100 different sources, cleanse it, bring it together and push it out for the Seeker front-end to share.
Bragi is a Data Warehouse (DWH) automation utility allowing you to consume, model and export data in a rapido fashion.
Rattling through the typical data flow for a DWH…
- Load - Bragi allows you to quickly pull data in to the DWH from other databases, flat files (xls, csv, text delimited, xml, a n other), web services, json, pretty much anything.
- Archive - Once we have the source data loaded into the DWH Bragi will then allow you to archive that data (so that you can determine what it looked like at any point in time).
- Model - Bragi allows you to create data models, typically building upon your archived data. You are able to build complex models step by step, shaping and transforming the data using a staged approach.
- Exports - If you need to produce text extracts, Excel exports or even push data out into an external data mart / sql database, Bragi will allow you to easily do so.
- Schedule - All of these steps can be automated using Bragi’s scheduler
- Every field has data traceability allowing you to quickly assess the impact of making changes (or having changes imposed upon you by upstream source systems).
You can find out more details on the Bragi site.
I’ve spent a large portion of my professional career building out data models, producing reports and extracting the gold from the raw data. Bragi is such an awesome tool that removes much of the monotony and tedium, allowing you to focus on the value add.
I’ll pull together some posts working through some examples and show this off.