Tag Archives: data science program

Data Science

Management Tips for Data Scientists

Posted on by Monika Wahi
When working in data science, there are some tips and tricks to managing your communication and relationship with superiors that can help you advance in your career.
23
Mar

Management tips for data scientists can be used by anyone – at work and in your personal life! Get the details in my blog post.

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Data Science

REDCap Mess: How it Got There, and How to Clean it Up

Posted on by Monika Wahi
REDCap mess on your hands? The REDCap designers made the application so loosey goosey, you can really program yourself into a messy corner if you don't plan well.
07
Mar

REDCap mess happens often in research shops, and it’s an analysis showstopper! Read my blog post to learn my secret tricks for breaking through the barriers and getting on with data analytics!

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Data Science

ETL Pipeline Documentation: Here are my Tips and Tricks!

Posted on by Monika Wahi
This blog post shows you how to properly document your extract, transform, and load code.
22
Feb

ETL pipeline documentation is great for team communication as well as data stewardship! Read my blog post to learn my tips and tricks.

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Data Science

AI on the Edge: What it is, and Data Storage Challenges it Poses

Posted on by Monika Wahi
AI on the edge refers to doing the AI processing and equations at the site of the object collecting the data.
06
Jun

“AI on the edge” was a new term for me that I learned from Marc Staimer, founder of Dragon Slayer Consulting, who was interviewed in a podcast. Marc explained how AI on the edge poses a data storage problem, and my blog post proposes a solution!

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Public Health Alphabet Soup

US Public Health Alphabet Soup Explained: What is the IHS?

Posted on by Monika Wahi
The Indian Health Service (IHS) is the federal agency in the United States in charge of reservation health.
22
Apr

“What is the IHS?” is a reasonable question to ask, because there are a few things that are very special about the IHS and its healthcare facilities. At first glance, these special characteristics may seem positive, but they actually have devastating unintended consequences, as I describe in my blog post.

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Data Science

Making Box Plots Different Ways is Easy in R!

Posted on by Monika Wahi
There are two main ways to make box plots in R, and this blog post shows you how, and explains the differences.
31
Mar

Making box plots in R affords you many different approaches and features. My blog post will show you easy ways to use both base R and ggplot2 to make box plots as you are proceeding with your data science projects.

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Data Science

Convert CSV to RDS When Using R for Easier Data Handling

Posted on by Monika Wahi
If you want to use R for a project and the source CSV is very big, it can improve input/output efficiency to convert the file to an RDS.
25
Mar

Convert CSV to RDS is what you want to do if you are working with big data files in R GUI and want to improve efficiency. Read my blog post for an explanation and video demonstrations of this process!

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Data Science

GPower Case Example Shows How to Calculate and Document Sample Size

Posted on by Monika Wahi
This case example shows a use case where we estimated sample size in GPower under different conditions.
18
Feb

GPower case example shows a use-case where we needed to select an outcome measure for our study, then do a power calculation for sample size required under different outcome effect size scenarios. My blog post shows what I did, and how I documented/curated the results.

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Data Science

Variable Names in SAS and R Have Different Restrictions and Rules

Posted on by Monika Wahi
You need to come up with names of variables in SAS and in R, but they need to be compatible with both languages if you are running a data warehouse.
04
Feb

Variable names in SAS and R are subject to different “rules and regulations”, and these can be leveraged to your advantage, as I describe in this blog post.

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Data Science

Referring to Variables in Processing Data is Different in SAS Compared to R

Posted on by Monika Wahi
When doing data processing, especially extract-transform-load (ETL) into a data warehouse, you might need to refer to the variables in your code, and it's done differently in SAS vs. R.
28
Jan

Referring to variables in processing is different conceptually when thinking about SAS compared to R. I explain the differences in my blog post.

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