Join Robin Hunt for an in-depth discussion in this video Truths, part of Learning Data Analytics.
- So, I love data. I eat, sleep, and breathe it, actually. I know because of this and my experiences with data and people, that there are several types of truth. Maybe even more. So the truths are: The data truth, the stats truth, and the business truth. The data truth is literally what shows in your data results. The stats and the researcher truth is what the significance is of the data and the impacts. And then the business truth is how the business interprets the data and makes decisions.
On the data truth, you created your results. You verified the results. You're truly showing the data truth. What the data shows. It's important to understand though, the data truth can be deceiving. Sometimes not all the data's been entered. Sometimes the historical data's not represented properly. And sometimes people just haven't gone back and done their updates yet. Then you have the stats and the researcher's truth. You have the data and the numbers, but the stats truth can be related to the significance of the numbers, and how likely this is to be a valid result versus a coincidence.
Researchers are the most happy when the impact is significant in a positive way, and your data is tested not to be a coincidence. The business truth is one of the hardest realities for a data person. You can't control the business thought on your results. You can only deliver the data. Remember your goal as the analyst is that the truths you encounter can create positive impacts for better decision-making. Just be aware that there's a data truth, a stats truth, and a business truth.