Context and problem. You have terabytes of structured data, petaBytes of unstructured data, that are not quite visible, and many areas are dark, they provide less valuable information. You have lots of dark data, but not a whole lot of insight. How can you not only see summaries and means and graphs of trends, but to gain insight, that you can count on to associate specific value-adding business activities and based off of them, make strategic business decisions. How can you shine light on all the dark data that is sitting in those ObjectStores, relational databases, datawarehouses, content stores, voice, images, text,....
Considerations. Leveraging data, through analytical processing is not just about processing structured data often residing in the organization's many systems of record or transaction-processing or even online analytics processing databases. It is rather about the ability to combine unstructured data coming in either from IoT devices, which are semi-structured data, and from content-based (think Enterprise Content Management (ECM)) systems that contain images, attachments, documents and text in free format.
Solution Path. Extracting data from unstructured content or text from images, transforming semi- and un-structured content into structured data, storing it in a DataLake and possibly into other Case Management systems, will allow you to start gathering the raw data you need to start your curation and data wrangling.
Then you can apply Data Science and Machine Learning to the curated Datalake to gain insights, and incorporate the conditional actions you wish to take as part of a BPM or Case Management solution. Alternatively you can wire a set of micro-services via APIs exposed from Software as a service vendors, to evaluate the insights and based on certain thresholds, invoke a workflow or display a result for human knowledge workers to take action.