In ancient times, long before Gutenberg invented the printing press and Tim Berners-Lee invented the World Wide Web, oral tradition would prevail, and the skill of storytelling was a critical one for the transmission of knowledge in society. But now that we have printed books, Web pages, and even wikis, why would businesses need to resurrect this ancient form of communication?
In today's world, our challenge is not to get data, it's to get the right data. And yet not all executives have the time, or the skills, to understand this data. Hence the need for a data interpreter, also known as data story teller and one of the 5 hottest jobs in data today, who will help them in the following situations.
Too much data
We have all heard the saying: the tree that hides the forest. What about: the forest that hides the tree? The modern data infrastructure, organized around the data lake, enables (and encourages) the collection of any data set that is available to collect, regardless of its relevance, trustworthiness, or origin. Therefore, making sense of all this data requires specific expertise in the business processes and in the data collection mechanisms. You may very well be getting reports and exports but the role of the data story teller will be explain which data makes sense and which is just noise.
Not enough context
The other downside of the data lake is that there is no provision for metadata. This is one of the biggest gaps in the big data stack, along with security. And even though vendors are working hard to remediate this flaw, there is already of lot of hard-to-control data out there. Understanding the origin, lineage and reliability of data is essential, and apprehending its actual meaning is critical.
There is an old joke among business intelligence professionals, which consists of figuring out what "revenue" means for finance, for sales, for marketing, for legal, etc.: even working from the same raw data they always come up with different results. Imagine what happens when the source data is not well tagged? You'll need help, you'll need someone who can tell you the story.
Need for special skills
Some data cannot be understood without specialized skills. If you are not a biologist, try to make sense of drug test data. If you are not an aeronautical engineer, flight parameters are probably tough to understand. Before big data, this would rarely be an issue because specialized data was only available to experts who would present it synthetically to business executives. But when such data ends up in the data lake (in order to look for correlation with other data sets), someone is going to end up looking at it. Getting assistance from a field expert -- a specialized story teller -- is probably a good idea.
Poorly designed reports
Of course, there will always be a case where a good story teller is a must-have: when reports are not top notch. Modern business intelligence tools provide tremendous capabilities to alleviate the pains of reporting, providing excellent user experience and intuitive data navigation. But a great tool is only helpful if the people using it are equally great.
For the foreseeable future, I predict data story tellers will continue to help executives read poorly designed reports!
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