Best practices for Big Data
A good Big Data architecture combines DWH, BI, Hadoop and Real-time technologies. Hadoop isn’t going to replace your enterprise data warehouse, and big data analytics can not replace existing business intelligence infrastructure. To make the most of your data, you will need all these proven and new technologies working seamlessly together. However, not depending on technology, the analytics solutions are most successful when approached from a business perspective and not from the IT/Engineering end. Choosing the right technology and architecture from all the options is a crucial and difficult problem.
How we work
We work in agile fashion, following Scrum methodology. This gives you full visibility and control over the development process. It allows us to react together to changing conditions, taking advantage of new opportunities as they are revealed by working with your data.
We prefer to "start small", by limiting the scope of the initial deployment. Once the solution is working, we extend it step by step. This approach offers several advantages: starting small is less expensive, it avoids big risks, it is more flexible and less stressful for project stakeholders.