Data science seems like a brand new term but isn’t so. We have always had data science – typically defined as principles, processes and techniques to understand the world around us through analysis of data.
Sometimes, data analysis does not necessarily result into decision making. So what do we need to do to get become a data driven decision making organization? First step is to understand what is generally involved in data science and data driven decision making.
I would have to say that there are two types of data based decisions groups generally identified –
- “Discover” or understand data: This group is often ignored or is not identified as a key element by most organization. This probably comes from a place of hubris – “well, we know our data well!”. However, the new norm (and the fact that more data are available) is to continuously discover data.
- Decisions that repeat: This group is very popular candidate when it comes to data driven decisions. Customer churn is an age-old problem that has haunted even the best marketer.
During the past few years, we have seen tremendous improvements in technology and the natural rise of “Big Data”. So how can we make use of these advances, think analytically at a massive scale and process giant volumes of data on a daily basis?
I will summarize the data processing challenge (and a few solutions) in the next post. Stay tuned….