Why ‘data mining’ is limiting term for Data Analytics?

A person mining for iron is called iron miner, mining coal is called coal miner, mining gold is called gold miner. Does ‘data miner’ mine for ‘data’?

Twenty years back, Mr. Pushpraj Soni was one of the only few goldsmiths in my town. He loved his craft, creating delicate gold jewelry and embroidery of gems. One day, a young customer called him ‘metal worker’. After all, gold is a metal. In couple of minutes, the customer was thrown out of the shop. Mr. Soni didn’t buy his generalization. He explained, “I create monuments of love and pride from gold. I am goldsmith. Calling me a ‘metal worker’ is demeaning.”

All professions are identified by their output, not their input. Pottery maker is not same as clay maker. In data analytics, data is an input, not the output. There are multiple steps involved and the final outcome is definitely, not ‘more data’ or 'crafted data'. In Gold mining process, rocks are broken, crushed, filtered, crushed again, more filters, ore is segregated, melted and then finally gold comes as output. It is a long process, multiple iterations, all clubbed under term as ‘Gold Mining’. Isn’t calling it ‘Data mining’ akin to calling ‘Gold mining’ as ‘Rock mining’?

What is the output of data analytics?

As human, we seek balance or ‘Coherence’ between self and surrounding. We form a story to provide this coherence; called as ‘Narrative Identity’. Extending this analogy from individual to human collective, called ‘Business enterprise’, we have ‘Business Narrative’.

While applying analytics for problem solving, data analysts seek out most ‘credible’ explanation. They want to find most plausible ‘narrative’ which can explain the situation, considering all historical events and possible implications. Akin to human narrative identity, analytics dig in to business narrative and magnify or suppress specific parts. It is story of human collective. Data is filtered for these ‘stories’, ‘snippets’ which can make collective actions more coherent.

‘Data miner’ does not exist. There are only ‘Story Miners’.

Data analyst or scientist seek out human stories, through most objective language humans have ever created; ‘mathematics’. Data analytics owns skillset to make a business, more human. It is a long process akin to gold mining, with lot of repeated crunching, sorting and filter. Though, we should not forget the final part of Goldsmith. A good story becomes great and part of Business Narrative when put in right application. I term this value add as ‘Storysmith’.

What is different in data analytics from market research? It is same difference between a person, mining gold from huge gold mine and a person panning gold from river bed sand.  

What do you think, is ‘data mining’ the right term for Data Analytics?