This is our lifeblood. It's what we were founded on: a love of putting order to chaos. Transforming data from a raw state into rich analytical resources. Making it flexible. Fast. Bringing answers to people who need it.
With our Extract, Transform & Load (ETL) Database Engineering services, we'll help you choose a path that will maximize benefits for your organization's short and long term analytic needs – with minimal risk. And we'll help you implement this choice cost-effectively with open source and other technologies.
We'll model the right kind of database. For the right need.
Data Warehouses. Data Marts. Operational Datastores. Kimball. Inmon. Type 1, Type 2, Type 3, Type 4 slowly changing dimensions. You name it. We've done it all. We've done it so much that we know there are many database types and designs to serve many purposes. We know all the rules. Let us show you how you can follow some of the rules, and break a few others...to your benefit.
We'll cook up some ETL. Or maybe even a tasty little ELT (with a side of mayo.)
We've done data integration a lot, so we know the options and how each perform. We'll implement the right data transformations for you, your systems, and your database of the future. We'll deal with change data capture issues, data quality, metadata management, incremental load processing, and so much more. We'll put it into production and make it easy to administer, so it's not the headache it once was.
We've got a number of technologies we like to use. Some of the open source projects, like Pentaho Data Integration, can get you a lot of value for a small investment. All of them have flexibility to do whatever model best works for the kind of data you are collecting, and the kind of place you're storing it in.
Stay classy, data warehousing.
It's not cool to talk about data warehouses these days. There are new sexy technologies out there. Many folks have invested a lot in this infrastructure, and see it as slow to change. All of this is true, but we've been around long enough to know that it's not so black and white. Data organization is essential to derive meaning. Ultimate flexibility has to be balanced against a common language. The data engineering work we do reflects this. We aspire for maximum flexibility, but also want to be grounded in some solid data management principles.
Classic data warehousing architectures revolve on relational database standards like Oracle, SQL Server and MySQL, but we'll also use the new class of high performance analytic databases, like Vectorwise, Netezza, Amazon Redshift, and others.
The elephant & the data warehouse.
Part of modern ETL is recognizing and being able to take advantage of modern data platforms, like Hadoop, MongoDB, Cassandra, and others. Not every next generation platform solves everyone's needs, but your data management layer sure needs to deal with it. When we do ETL projects, we're sure to pick the right technology to do not just one flavor of processing, but many flavors. Because the number of data sources in your company sure isn't decreasing.