Why Data Engineering?

Data engineering is a practice, a strategy, a discipline that creates consistent and reusable answers about data.

• Repeatability, automation, and comprehension
• A roadmap for exploring and answering current and future questions about “all your data” with clarity across disciplines and roles.

Will “more tools” fix your problems?

Communication between human beings that yields shared understanding elucidates and fixes issues.

Tossing yet another analysis tool on the pile or porting to a new database platform isn’t going to “just fix things”.  Why, how, at what trade off, and at what cost?

• You can get a handle on it.  You can do so affordably.
• One size (or approach) does not fit all.  Data engineering strategies must adapt to you; not (always) “trends in the I.T. industry”.
• When resources and heavy lifting are needed you need the right help in the right way - on time.  We can:
  • help you prepare quotes to bid out services.
  • help you prepare specifications and define scope.
  • insource resources and do the work for you / with you.

Things we’ve done / Things we do

• Data engineering project management
• Data dictionary construction / concordance generation
• RESTful API construction: Swagger, AWS API Gateway
• Data workflow (and pipeline) automation: scheduling, audits, logging, monitoring, and alarms included
• Extract, transform, and load (ETL) scripts and processes
• Object relational model design and implementation(s): Entity Framework, Hibernate, SQL Alchemy, Doctrine, etc.
• Warehouse database construction: local (customer premises) and/or Amazon Redshift
• We work with any data source(s) and desired data destination(s)
  • regardless of platform
  • regardless how old (or young) the technologies and approaches you employ

Together we will formulate a strategy.  Partner with us.