
… of not only prioritizing and specifying workflow focused solutions but also data-driven solutions. The delivery of data-driven solutions demands longer-term planning and often more capital-intensive investment. The processes also change with more complex development cycles and changes in ongoing maintenance.
When I dig deeper, I often find that the team is having to “reinvent the wheel” each and every quarter. There’s a mad rush in the final days of the quarter to fine-tune objectives, “come up with” key results, and make sure it all “ties together up and down the organization” (while simultaneously doing actual work). In short: painful and disruptive, or as an engineering manager once described to me “planning masoc…
There are a large number of reasons why you might want to transform your data, but they all boil down to this: it’s a good idea to apply a certain amount of business logic to your data before users get their hands on it. Remove erroneous records. Fix data anomalies. Translate old business rules into new ones. Generally apply business logic that will make it easier and more consistent to analyze data once an analyst actually sits down to their keyboard.