A process to find specificity as part of market or user research by utilizing WHAT and WHY.
ETL stands for extract, transform and load. It is a common methodology used by data teams to find insights from data. We need to perform these three tasks at some point when working with data. But, what often happens with our data gathering tasks is that we lose the context of our subjects and end goals of our hard work. The final result is incorrect, low-value insights that do not have much business value. We end up spending resource and money on wasted tasks. The gap between high-value and low-value insights widens.
But there must be a better way to find insights that are high-value, context-driven.
The answer is to ASK before you step into the Extract Transform and Load stage. The more time you spend on the ASK process, the more time you can save on the ETL process. In addition, the insights you will bring to the team will be highly actionable, focused and of high value. I have learned the efficiency of this process through trial and error while working with data sets. Hence, when I get a new data analysis project, I spend more time mining and understanding every requirement. I ASK additional questions to synthesize my understanding, clarify the deliverables, know how it will be utilized and in what context before even starting the data acquiring process.
Now let’s have a look at what really is the “ASK” process…
ASK process is simply a list of a few questions you will ask based on the details or instructions you are given by your customers/stakeholders/requestor.
ASK includes 2 keywords: WHAT and WHY. Before you start to even extract data, ask yourself what are the problems you are trying to solve and why you are trying to solve those specific problems. This will quickly connect your thoughts with the overall goal/outcome of the project.
Use this tactic: I am trying to (insert what) in order to (insert why)
Example: My manager is trying to understand the negative sentiments of the Arizona customers related to our new product X in order to improve the product quality and pricing.
The key (ASK) words here are: understand, negative sentiments, product X, Arizona, quality, pricing. Further questions you can discuss with your team to clarify the context, perspective, and understanding of the requirements before doing any analysis could be:
What do you mean by “understand”? Are you trying to find any certain negative feedback or value? For example: Are you trying to see who rated the product exactly 3 out of 5 or at least 2 out of 5 etc. What is your baseline for the negative sentiment in the first place? The point of ASK is to clarify assumptions.
ASK strategy will not only help you with what to find but also how to find it. It will create a roadmap for the research process- saving time, resources, and money. Rest assured that your insights will be powerful and on point.
Time is money, and data is abundant. ASK before you ACT to save yourself time and money. Together we can conquer to find great values from hidden data.
I hope my ways of dealing with data help define yours.
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