My name is Data
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I was born when a retail customer swiped her debit card against a card swiping machine, my biological mother. My name is Kate alias 'Data'.
A nurse, an MQ messenger, took me to an incubator called middleware for a brief period to figure out where shall I live. Another nurse, an SQL programme, came running to tie a ‘Tag’ around my wrist. The tag contained where was I born, when was I born, etc.
Later on, I moved to my home, a "Transactional database". A strong compound wall surrounds my house. We call that a firewall. My grandparents, who were infra and platform engineers, built the house. My father, a DBA, made sure that the daily routines did not overload me with excessive reading and writing. He is very nice!
My uncle, a network engineer, used to manage the firewall and my aunt, a security expert, created keys to open the gate. Everyone around me was making sure that I was safe. I was indeed treated like a Princess! My cousin, an ingestion engineer, used to drop me off wherever I wanted to go. We all lived together as a joint family, and we were called IT.
When I was 7 years old, I went to a dance class in a nearby place called a “Warehouse”. The choreographers, an ETL developer and a data modeller, transformed me into an excellent dancer. I copied a version of myself in the warehouse.
Post my schooling, I went to "Lake" college for my graduation. My experience in the college was beautiful. The best part was that no one expected me to transform. I made many friends in college. Above all, I met my husband, Bill.
Bill introduced himself as a data analyst from the “Business” family. He was handsome and an excellent communicator. I was very much impressed and fell in love. We got married soon after graduation. Life was cool in the initial years. He respected me for who I was. He used to say that I was the most important person in his life, that he would decide nothing without me and so on.
On one weekend, he requested me to showcase my dancing skills to his extended family. We worked together for almost a year to perform on the stage. What I gained in the warehouse project benefited me. We announced that event ‘Dashboard’.
Everybody enjoyed my show. My husband was on cloud nine.
Things were smooth until my husband showed his true face. I figured out that he was not just a data analyst, but a ruthless data scientist. I found out when he introduced me to Sandra at a birthday celebration. Sandra was an algorithm that data scientists use in their work. He said that Sandra could predict the future if we train her. His expectation was for me to train her. Sounds strange? But that’s what transpired.
A week later, we started the training. Sandra was very assertive. The day the training started, she started spotting weaknesses in me. She mentioned I lacked completeness. I was not like others. I had mood swings, and so on. She said she will not work with me until I correct all that she mentioned.
My husband acknowledged her views and asked me to correct all that she pointed out. My response was ‘I don’t know and I can’t’. Sadly, he didn't listen to me. He replaced missing values with the ones he wanted. In the name of healing my mood swings, he got rid of outliers. To make me look like others, he performed standardisation.
I went through several training programmes with Sandra. After every training, he validated her learning. This cycle went on for several months until my husband was pleased with her learning and predictive capability.
He went to his family members and introduced her as a model. Yes, he called her a model. That’s what genuinely disheartened me. A model ? After all, I trained her. Why is she given so much importance? Has she become more important than me? Data or model? Time will tell!
I hope Kate's story has given a high-level understanding of two families in her life, i.e. IT and Business. How her IT family helped shape her life before marriage and how business relies heavily on her for decision making. This story also tells us how many roles are involved in capturing, securing, transforming, moving and storing data before it is consumed by analysts and data scientists. The list is not an exhaustive one though.
Investing in the data Vs model is a dilemma every business leader experiences regularly. Most often, the model wins primarily because the analysts & data scientists are closer to the business. What's your take on this?
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Views are personal and in no way reflect my current & previous organisations and vendor partners.
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