Network analysis is an amazing tool for business analysis.

But there are a few challenges to be prepared for.

#datascience #rstats #businessanalysis
Network analysis has the potential to identify the most influential customers for a business...

But there are a few challenges that the Data Scientist needs to be prepared for.
One that I often struggle with is determining the right threshold for showing network connections.

Too low and it becomes difficult to find the most important clusters.

Too high and there aren't enough connections to tell anything.
The cool thing is that I want to share how I actually do this in my network analysis process...
I have a FREE Network Analysis for Business Workshop where I will share exactly how to find the most influential customers in business transaction data...
And I'll go through my FULL PROCESS for how to isolate the most important clusters of customers so your company can profit (and customers will love it).
Reserve your spot for my Free Network Analysis for Business Workshop.

Discover how network analysis can be applied to your company's business data AND get a free cheat sheet that consolidates 20,000 R packages.

bit.ly/network-2

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More from @mdancho84

Oct 9
90% of data scientists are overlooking this skill for business analysis.

Yet, it's a gold mine.

Here's why...

#datascience #rstats #business #excel
Whether you realize it or not, your business runs off of customers.

And how they work is based on principles of social psychology.
If you understand which are the most influential customers, then you know how to market to them...

...And knowing their triggers is like adding fuel to a fire. 🔥
Read 8 tweets
Oct 8
Modeling in R is extremely powerful for business analytics...

But many beginners get stuck.

Here's my simple 3-step process to make a linear regression model in R. 🧵

#datascience #business #R #rstats Image
To give some background, these simple 5 lines of code create a basic business solution...

... I'm modeling my ...

Target = bicycle product prices (regression task)
As a function of my predictors:

Predictors = product categories (mountain or road bikes) and bicycle frame material (aluminum or carbon fiber).
Read 10 tweets
Sep 30
The more I dive into Bayesian, the more... my mind is blown.

Here's why. 🧵

#rstats #python #datascience Image
First, Bayesian is like normal regression. Except way better!

It literally solves issues in-sample by sampling. Lots of times!
Second, confidence intervals are realistic.

Unlike normal regression, Bayesian regression accounts for changing variance.
Read 5 tweets
Sep 30
No computer science degree?

Here’s how to get a job in data science. 🧵

#rstats #python
Learn these:

1. A programming language: R or Python

I chose #R because it was intuitive coming from a business background (excel)
2. Statistics & Math

Learn the basics of frequency, distribution, & within group analysis.
Read 10 tweets
Sep 29
My biggest mistakes were never in my insights.

My mistakes were in overconfidence. 🧵

#rstats #datascience #python Image
In business, I've made great regression models that have predicted how much sales we were going to make.

In fact, this helped me increase revenue from $3M to $15,000,000 per year at one of the companies I worked at.
BUT my models were NOT perfect.

In fact, I'd argue that the BIGGEST flops were due to overconfidence.

Believing my model was better than it actually was.

Things that hurt me:
Read 11 tweets
Sep 27
Why does every beginner data scientist fall for the "deep learning trap"?

True story 🧵

#rstats #datascience #deeplearning
When I was first learning data science this cost me at least 6-months. Seriously...

I was building a model for predicting which quotes would become orders.
I had just finished using a linear regression (didn't know about logistic yet) to make a predictive model.

Yeah I know - I was a noobie using regression instead of classification. So what?!
Read 15 tweets

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