DavidSietz
David Sietz is a solutions architect at International Association of Privacy Professionals with more than 25 years of hands-on experience. Starting his IT career in Munich Germany, his professional history as a data architect, system designer, and adult educator, instilled in him a sense of IT with the business customer in mind.
David's specialty is architecting, designing, and constructing of viable solutions that are properly engineered for their purpose and longevity. His breadth of knowledge of data management, microservice architecture, and building cloud platforms allows him to bridge disciplines and provide MVP solutions.
[Github Repo](https://github.com/dsietz/open-source-model) --- Open source is growing with leaps and bounds. Even corporations are adopting the open source products and reaping the numerous benefits. But there’s more than the products that need to be adopted – the Open Source Model itself is also highly valuable.
[Github Repo](https://github.com/dsietz/test-data-generation) --- Continuous Integration has redefined our testing practices. Testing has become more focused, efficient, and re-positioned further upstream in the development life-cycle. Unfortunately, our testing systems haven't evolved in lock-step - specifically the provisioning of realist test data. It remains common practice to extract, cleanse and load production data into our non- production environments. This is a lengthy process with serious security concerns, and still doesn't satisfy all our data content requirements. What if there is a better way of providing realist test data? What if it could be generated on-demand as part of the Continuous Integration process - without the heavy databases and traditional batch jobs?
[Github Repo](https://github.com/dsietz/daas) --- Should Information Management systems apply the services architecture? Many data provisioning and BI systems are monolithic, tightly coupled, difficult to scale, and stumble when it comes to delivering MVP in a timely manner.
[Github Repo](https://github.com/dsietz/daas) --- Data as a Service delivers MVP of real-time data management, while avoiding many of the anit-patterns that traditional data provisioning and BI systems portray. However, building out a Data as a Service system doesn't require high up-front costs and the welding of multiple products. Learn how the open source product Talend Open Studio can be used to build out a DaaS system that delivers faster and more scalable solutions to your customer.
Zero fluff.