A new blog series by DI’s George Dealy.
In this blog series, which I’m calling Practical Analysis, I’ll explore the emerging role of the analyst in helping to answer some questions that I’ll discuss below and in building a body of knowledge to take advantage of the data deluge. Hopefully by the end, you’ll be completely jazzed about your future as an analyst!
1. Numeracy: Analytical Skills for the 21st Century
If you’re involved in any way with analyzing information, you undoubtedly are acquainted with the term “big data” by now. There is certainly a proliferation of electronic data becoming available in increasing abundance. But just because there’s more of it, is it really that much different from the data we’ve had right along? I’d argue that the basics are still very much the same but with the addition of both rich possibilities for finding meaning and daunting challenges for filtering out the noise. Follow the link below to read my first blog on the subject of numeracy.
2. Learning from the Experts
In the first post of the “Practical Analysis” blog series, I suggested that numeracy will become an increasingly essential skill set in the 21st century, and that everyone, in one way or another, will become an analyst. But what does it actually mean to be analyst? There is no one answer. The possibilities range from someone who uses a working knowledge of analysis in their day-to-day work to hotshot data scientists at companies like Amazon and Google. Let’s say you want to begin your journey to become an analyst. Where would you start? Like with most endeavors: with the fundamentals, of course. To help outline those fundamentals, I have assembled a panel of experts.
More in this series to follow…
3. Statistics Help us See the Grey
Where do statistics fit into the world of analysis? Well, analysis allows us to make objective arguments to discover the truth based on actual observations – that would be data – as opposed to subjective claims based purely on intuition or potentially biased points of view.
But observed data still comes with an inherent degree of uncertainty. Where math tends to be “black and white” precise, statistics deals in the realm of “gray.” Statistics allow us to factor in uncertainty so we can draw meaningful conclusions with confidence. In this blog post, we will take a look at statistics’ fundamental concepts and tools.
4. Our Statistical Toolbox
In Part I of my Practical Analysis series on analysis and statistics, I talked about statistical concepts. Understanding the concepts is essential, but we also need to know the tools to put them to work. Here we discuss tools for applying statistical concepts and the importance of using the right tool at the right time.
5. How to Separate Noise from Meaning in Big Data
When we rely on data to make decisions, how do we tell what is a meaningful signal and what is merely noise? Data is neither, in and of itself, as Stephen Few reminds us in his latest book: “Signal: Understanding What Matters in a World of Noise.”
6. How to Harness the Power of Pictures in Analytics
As an analyst, you can perform the most sophisticated analysis and draw the most compelling conclusions, but without a way to share these with others, your hard work stays with you. So how to best communicate when it comes to quantitative data? In a nutshell: words and pictures.