I like frameworks -- it helps structure your thoughts. One of the most basic questions that I have asked looking at a company/org is to figure out how to evaluate the whether it's good or great? And more importantly, how to help drive it to greatness? There's a list of things that I could rattle off but it was not complete and also, I didn't really have a structure. [ 65 more words ]
http://insightextractor.com/…/framework-evaluate-great-com…/
As an analyst or data scientist, its important to have a holistic view of the org that you support. This is important because it will help you in metrics design, project prioritization among other things! Also, there’s a lot written on what is vision, mission & strategy and the difference between each of these. So this post is not a recap of that but I wanted to share an easy way to remember them: [ 53 more words ]
http://insightextractor.com/…/an-easy-way-to-remember-visi…/
We are heading towards the world which can either destroy or if we give it enough time, then we will have super intelligence!
I was invited to lead the office hours for the Springboard's Data Analytics for Business course and I wanted to share the recording with you all: I answer following questions during the office hours: What tools have I used in my career for Data Analytics & Data Science? What are the different analysis/modeling that you do? What are the biggest challenges that I found when I got in this Industry? [ 82 more words ]
http://insightextractor.com/…/springboard-data-analytics-b…/
Insightful talk on connecting purpose, mission & strategy together to make hard decisions. https://youtu.be/PtRVIp_e2bs
Great article on doing #datascience right:
[Blog] News: Stepping down as chapter co-leader #SQLPASS #Analytics @passbavc
http://insightextractor.com/…/news-pass-outstanding-volunt…/
What is the difference between courses offered by Springboard vs datacamp vs dataquest? Which is better?
http://insightextractor.com/…/difference-courses-offered-s…/
Get $100 off any Springboard course
http://insightextractor.com/…/get-100-off-springboard-cour…/
2017 #internet trends report | #Code 2017 https://www.youtube.com/watch?v=UC8GwG6srqs
#PowerBI idea: Enable #PowerQuery Excel add-in for Mac/Apple/iOS
http://insightextractor.com/…/powerbi-idea-enable-powerque…/
Microsoft ran a one-day workshop focused on #AI that I had a chance to attend last month. Here's the keynote: https://channel9.msdn.com/…/AI…/Keynote-Serving-AI-with-Data and here's the code from all four workshops: https://github.com/Microsoft/AI-Immersion-Workshop
[Blog] Analytics Framework by Rumsfeld #DataScience #DataAnalyst #Analytics
http://insightextractor.com/2017/…/18/rumsfeld-on-analytics/
If you are a data & business intelligence professional and haven't heard about bots, you will soon! Most of the big vendors (Microsoft, Qlik, etc) have started adding capabilities and have shown some signs of serious product investments for this category. So, let's step back and reflect how will bot impact the adoption of data & business intelligence platforms? and why you should care? [ 776 more words ]
http://insightextractor.com/…/will-bots-impact-adoption-da…/
Great post!
Almost all practitioners of digital analytics measure the same 10 metrics, regardless of the type of business. In my new post, I take 15 companies and identify ...6 KPIs for each.
"The Very Best Digital Metrics For 15 Different Companies!" https://goo.gl/nNh07R
Here are the companies I share recommendations for: Betabrand, Lefty's Sports, Salesforce, Tampa Bay Times, The Smile Train, Humira, California DMV, Shutterstock, The Fate of the Furious, Jam City, Nissan Sunnyvale, McCormick, Dell US, Prudential and Priceline.
Enough differences in each for you to sharpen the critical thinking you can bring to your own company. Along the way, you'll discover new valuable metrics that you might not have paid as much attention to.
Learning via actual use cases, here: https://goo.gl/nNh07R
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: Spreadsheet modeling Forecasting Customer Segmentation Root cause Analysis Data Visualization and Dash-boarding Customer Lifetime value A/B testing Web Analytics VIEW QUESTION ON QUORA
http://insightextractor.com/…/must-know-software-skills-ca…/
Lean Analytics is one of the best resources out there for anyone doing #analytics & #datascience
