SF Data Weekly - Kids and Data, Lessons from Delos, and R before Python

Introducing kids to data using data visualizations, with activities you can use with your kids.

How to use a new cloud-based Python Data Processing Engine.

One of Salesforce’s best features is its ability to run BI and analytics workloads to identify hidden trends and insights. So why not perform analysis from your many sources within Salesforce itself? Here’s how. [Sponsored]

Mahesh led the three-person team that built a core piece of Facebook’s production data infrastructure. He shares his lessons learned.

What are Data Lakehouses? Just another buzzword or actually the successor to Data Lakes and Warehouses? This post is a basic introduction to the concept.

An example ML project to predict churn using real-world telco data sourced from Kaggle.

A couple of use cases where R beats Python, from someone who formerly wouldn’t use R since he thought Python was better.

A full-stack data scientist shares how he determines whether a given project would be better served with visualization instead of machine learning.

After having explained how to read box plots to thousands of workshop participants, the author now believes that they’re poorly conceived.

How Pipedrive, a CRM company, set up a product analytics and usage tracking process.

Uber’s LedgerStore was an immutable, ledger-style database built on DynamoDB. How Uber migrated from this solution to an in-house, homegrown database.

What’s a BI Engineer? Read this piece to find out more about the role, and how it fits with other players in a company’s data infrastructure.