Data Analytics is not about the data... it's about the questions needing answers.
Frank Bergdoll
Helping others on their learning journey Instructor, YouTuber, Writer, and always curious.
We are once again on the cusp of graduating a new group of students from our Business Intelligence and Analytics program and soon I will be watching the final presentations of their case-study. Throughout the program, I have worked to convey how critical it is to begin any data project not with the data itself, but with the processes/questions that you seek to gain insight into with the data.
So often, I see a focus on tools or products to display, move, present data to an end user. What I really want to see is much simpler. A good question with a good answer.
Of course, that good answer needs to be factual and fact-based. Which is where the data comes in. We need to think about our ability to actually answer a question posed to us with the data at hand. Hence the need to do both business analysis (to uncover processes and questions) and data modeling (to find out what we are working with).
This is also connected to my own specific area of interest - how to make education more effective and put control of the process to where it needs to be: in the hands of the learner. With the help of supportative stakeholders such as parents (where applicable) and educators/administrator.
I was looking at this and found an article that may be of interest to others that are interested in data analytics in education.
https://www.oreilly.com/ideas/education-data-analytics-learning
Engineer|Knowledge Distiller|Strategist
6 年Good Read. First principles always! If you lock in the fundamentals, the tool you use is irrelevant, as the work your conducting is founded on adding insight and value. Much research, conducted by very smart people, end up with very little to take away at the end. 1. Understand the fundamentals 2. Define the objectives and goals of your efforts 3. Select the tools to achieve these goals 4. Succeed
Bridging Computational Science and Precision Health
6 年The data science hype has resulted in the ambiguous "throw the data at it" stance in the growing generations. Ambiguous, because while it adequately captures the strength and the mission of data-driven/bottom-up approaches, it also neglects its counterpart, effectively precluding people from crystallizing the realization that data science is only as good as questions it is used to generate answers for.?
Communications and Content Expert
6 年Thanks for the share!
Director of Organizational Impact at YW Calgary - using data to improve impact every day
6 年I think it is true that for many new technologies we treat it like the old saying, "if you have a hammer, everything looks like a nail". We are actively looking for ways to apply the technology and demonstrate prowess. Often this precedes valid business questions that can be answered using the technology. Out of this shotgun approach however most technologies find their appropriate niche. Truly inspired technicians find the business niche more quickly and apply the technology more effectively.
Data driven decision making to create inclusive teams
6 年I actually had this very conversation yesterday!