Agile Data Engineering

Do you want to solve these issues?

As a Data Engineer it is your job to help your business partners drive growth and analytics play a key role. Do you find yourself thwarted by one or more of these challenges of analytics?

Agile Data Engineering Un-maintainable system

Un-maintainable system

You have produced some great Python and SQL scripts, but they are held together with twine and bubble gum.

Agile Data Engineering Data Errors

Data Errors

These creep in front of your customers and make you look bad.

Agile Data Engineering Error prone process

Error prone process

You find that there are too many steps that have to be done in the right order and it is hard to keep them streight.

Agile Data Engineering Too much work

Too much work

You cannot keep up with the requests from your business partners and they are getting frustrated.

Agile Data Engineering Great tools

Great tools

You see that there are lots of great tools out there and you want to take advantage of them, but it is hard to pick just one.

You have looked at or tried standard ETL tools, but you found their metadata driven approach has it limits and the tool's output cannot be branched and merged. Also, you have explored open source tools, but see they are not a complete solution.

How to succeed

DataKitche provides you the solution you have been looking for. The following chart shows how DataKitchen compares to open source and traditional ETL Tools:

Feature Open source (e.g. AirFlow) Traditional ETL DataKitchen
Orchestration of steps x x x
UI & Command Line x x x
Produces mergeable code x Not Usually x
Version Control Some x
Tests for data quality x
Tests for code quality x
Environments to work in x
Deploy Support x
Full support for Agile development x

You need to have the ability to move features from a dev environment to production with high velocity and safety -- to be more agile. You need to be able to quickly respond to request for more data integrations or more business logic quickly. You need to know when data goes bad so you can take corrective action and not have your customers call you and lose trust in you. You need to have your processes automated and quality integrated and not be locked into one tool centric approach. You need to be able to quickly iterate through the cycle shown below.

Agile Data Engineering Successful projects generate lots of requests.

Agile Data Development Solution

Our DataKitchen DataOps platform will enable you to quickly iterate and deploy new code and data sets while improving quality, unlike a patchwork of manual operations or a single vendor solution. DataKitchen makes your team shine by providing an end to end DataOps solution with minimal programming that uses the tools you love. In short, our platform will:

Agile Data Engineering Un-maintainable system

Orchestrate data to customer value

Run your favorite tool at the right time and run integrated quality checks to make sure bad data does not slip into your customers' hands or systems. Our platform also manage the code produced by your tools.

Agile Data Engineering Data Errors

Deploy ideas to production

Our platform will help you get your new ideas into production quickly by simplifying the process of branching & merging code, managing work environments, automating deployment, parameterizing the process, and promoting re-use.

Agile Data Engineering Error prone process

Automate and monitor quality

While orchestrating data to customer value or deploying ideas to production our platform provides a framework for automated tests so you can work with confidence.

Agile Data Engineering Speed ideas to production.

We recommend starting in the cloud and we can help you get set-up with our fast start service. Once set-up, the operations of the DataOps Platform can be easily and seamlessly transitioned to an internal team.

Agile Data Engineering Podcast

The Data Engineering Podcast with DataKitchen

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