All organizations have a different and unique starting point when it comes to the current state of their own data framework. Some have no overarching data strategy with data trapped in core operating systems, while others have a plethora of data strategies all in different states of completeness, technologies and capabilities. With the advent of cloud based big data platforms, the world has changed dramatically in just the last few years where comprehensive data strategies can be envisioned, planned and implemented in significantly less time and cost. This is mainly due to the shift from solely relying on 20 - 30 year old database technology utilizing structured relational data models instead of the more nibble and cost effective unstructured data models of a big data Hadoop framework running on a cloud based environment. What previously took years and often tens of millions in expense can be dramatically reduced to months and somewhere between one tenth to one sixth of the cost of using traditional technologies and approaches.
Besides leveraging the cost efficiency of a cloud-based framework and big data architecture, the concept of utilizing an ELT (extract, load and translate) as opposed to the more traditional ETL (extract, translate and load) approach can also lead to being more nimble and faster to market. This shift in focus takes the heavy lifting of translating data and moves it to the tail end of the process instead of it being an earlier hurdle and converts the translation more to a simple data exercise. This means that once the Investics data and analytics framework is in place the ability to start benefiting from the arrival of data is instant and empowerment is brought immediately to the appropriate stakeholders.