Think of “continuum” as something you start and you never stop improving upon. In my mind, Business Analytics Continuum is continuous investment of resources to take business analytics capabilities to next level. So what are these levels?
Here are the visual representation of the concept:
SQL, Excel & Tableau-like tools are good enough to start. Then add something like R eventually. And then there are tools that are specific to the industry – example: Google Analytics for the tech industry.
Other than that, you should know what do with these tools. You need to know following concepts and continuously build upon that as the industry use-cases and needs evolve:
I was at the HP Big data conference last week and I heard something during the keynote that’s worth sharing with you.
As Data & Analytics professionals, we spend a lot of our time on finding insights, trends & patterns out of the data but the keynote speaker (Ken Rudin, Facebook) encouraged everyone to take that a step further = Think about Driving impact based on the insights. It’s simple yet a powerful idea! Over past few months, I have started working closely with decision makers and helping drive impact vs just “handing-off” insights.
Don't strive for actionable insights but focus on taking it to next level: drive impact – Ken Rudin #HPBigData2015
Sometime back I worked on a research project that involved writing some R code – we were searching for tools ways to pull data from multiple social networks, perform text analysis and create effective data visualizations. R seemed like a great tool & so I was searching for a book/guides that teaches me fundamentals I needed to know to get few R related things done. One of the books that I used often during the research project was “R in nutshell”. I didn’t read it cover-to-cover but it was a great reference book for me. I used to read guides online/other-books and then I used to combine information from this book to get stuff done. The section I liked the most was on Data visualization which included some great code snippets to create effective data visualization using ggplot2 library. I used to take code snippets from this book & apply it on data-sets that I had.
Also, I liked it that the book has some end-to-end examples that cover the entire life cycle of data analysis/statistical-analysis.
I recommend this book as a “reference” for someone who started working with R.
I received a copy of this book as part of OREILLY’s Blogger program. Thanks OREILLY! If you are a blogger, you should check out that program!
And now, the 12 one hour sessions ranging from data visualization, predictive analytics to Big Data are online for you to watch! They also serve as “Trailer” for what you can expect at the PASS Business Analytics conference!