Building the technology stack

Once you have the business strategy aligned with your data analytics strategy, you can start thinking about the technology stack you will need. Instead of going with the latest and the coolest technology available, you need to align your data analytics strategy with your technology stack. You need to look at your current data maturity and plan your target maturity model based on the analytics required now and in the future. Think about the life cycle of the data as it enters your organization right up to the output it generates – ingestion, integration, transformation, processing, presentation, and archiving.

One of the challenges of modern-day analytics is that data now comes in different formats having different processing needs and processing speeds. Big data has semi-structured data processed on parallel Spark nodes. Transactional data needs to be transformed into OLAP cubes and processed by a massively parallel processing (MPP) data warehouse...