Digital Strategy Series Part I: Creating a Data Strategy that Delivers Value
Oh, the strategy pundits hate me! It’s not because I’m tall, good looking and from Iowa (well, 2 out of 3 ain’t bad), it’s because I think Strategy as a “Discip...
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How “anonymous” is anonymous data?
This post discusses what actually makes data anonymous, share about the misconception we have of it and describe the problems it raises. In the beginning, there was data ...
Visualizing Survey Data
In this post, we will be visualizing survey data for the top survey question types. I’m Tyler Lubben, founder of VizualSurvey, a survey data cleaning tool that cleans ...
ETL vs Data Preparation: What does your business need?
What is ETL? Put simply, an ETL pipeline is a tool for getting data from one place to another, usually from a data source to a warehouse. A data source can be anything fr...
Using Google Mobility Data to Model Covid-19 Case Infection Rates
Using Google Mobility Data to Model Covid-19 Case Infection Rates Paul B. Parker, Ph.D. Introduction The question of how and when to open up the economy as Covid-19 rates...
Dirty Data — Quality Assessment & Cleaning Measures
Practical guide to understand, build, and execute data quality & cleaning process In the book ‘Bad Data Handbook’ Q Ethan McCallum has rightly said, “We all say...
Johns Hopkins Covid-19 Data and R, Part I — data.table handling.
Summary: This blog showcases the handling of daily data of cases/deaths from Covid-19 in the U.S. published by the Center for Systems Science and Engineering at Johns H...
How to remove duplicates in large datasets
This article was written by Suresh Kondamudi. Dealing with large datasets is often daunting. With limited computing resources, particularly memory, it can be challenging ...
A Data Scientist’s Perspective on Microsoft R
This article was written by Lixun Zhang. As a data scientist, I have experience with R. Naturally, when I was first exposed to Microsoft R Open (MRO, formerly Revolution ...
Don't Buy Data – Invest In It
There are some expressions about data that are getting a bit tired: Data is the new oil; In God We Trust (all others must bring data); Buy data, sell high… Okay, yo...