Detective Data was having a tough morning. 3 cups of tea and snarling traffic congestion later, she had arrived at the location of the so-called disappearance but was no closer to finding the reason. She felt a deep personal connection with the case.
She looked up from her notes at the striking figure before her. Arrayed in multi-hued patterns, she introduced herself as “Visualization.”
“So, what was your last interaction with Insight?” Data asked.
“Why, a few days back, I showed her some stupendous new dashboards with the latest fancy charts: s—spider charts, c, candlestick charts and i, interactive charts.” Visualization shared, pacing around the room in colorful strides.
“And what did she seem like?”
“Well, she asked me if leaders really looked at any charts beyond the pie, bar and column. And she said something curious. More charts do not mean more Insight. So disappointing.”
Hmm…Death by dashboard? Data scribbled on her notepad.
Just then, the door flew open. Shimmering inside came in Gen AI.
“Heard you are looking for that Insight fellow. Need my help?”
Visualization had hastily vanished as if in awe of AI’s majestic presence.
Data looked up, mesmerized. But something tugged at her. Some old memory. Sipping a cup of tea, she found the notes from an old case and faced AI.
“Says here you’ve changed name and shape many times.”
“What’s in a name? You know what they say, ‘A rose by any other name would smell as sweet’ and all that?”
“Hmm.. Analytics. Big Data. Machine Learning. NLP. Are these your earlier monikers?”
“Maybe. Maybe not. Maybe they all just want to be me. Or part of this Gen next, me.” AI grinned confidently at Data.
“So, we were talking about Insight.” Data voiced.
“Ah, yes. Mysterious missing Insight. Most interesting. I remember we spoke. No matter how many models, codes, or even automated writeups I came up with for our client’s Business Problem, she just didn’t seem to agree with the solution. Very hard to understand, that one, I tell you.”
“And why is that?”
“Think simple with structured thinking, she kept saying. Our solution must simplify decision-making. Not complicate it.” AI finally seemed more bewildered than confident. AI veered back at her suddenly. “What’s your interest in this case, though? You seem quite familiar, you know.”
Data shivered. Everyone seemed familiar, yet so lost. It was like the Wizard of Oz. Is the wizard really the one with the answers? And who’s the wizard here? She thought to herself.
Meanwhile, Business Problem was beside herself with worry. She needed a solution, fast.
The room was empty once more. Data was looking at her diary. The notes danced in front of the eyes. Data. Analytics. Visualization. AI. Business Problem.
Insight was right there, within them, the invisible connecting point among all of them, the meaning they had lost on the way. It was time to face the Business Problem. She finally had the answer.