# Day: August 14, 2023

As data-driven decision-making becomes more critical in various fields, the ability to extract valuable insights from datasets has never been more important. One common task is to calculate counts by group, which can shed light on trends and patterns within your data. In this guide, we’ll explore three different approaches to achieve this using the powerful R programming language. So, let’s dive into the world of grouped counting with the help of the classic `mtcars` dataset!

Read on for the base R solution, the dplyr solution (which looks a lot like how we’d solve it in SQL), and the data.table solution.

This is fun It is also O(MAX) complexity. But first some background. Since the problem is super old, we are not intending to solve it, merely to play with it. In the number theory of mathematics, the Goldbach’s conjecture states that for every even integer (greater than 2) can be expressed with the sum of two prime numbers. There are also far cries from this theory. For example, prove that every even number can be written as the sum of not more than 300.000 primes (by Schnirelman (1939)).

Read on for the functions and trials of Goldbach’s conjecture.

There are some instances when you want to analyze data over time, not just dates. Most of us are familiar with having to create date tables and use them in analysis, but having to analyze data over time is not as common. Let’s say you run a taxi company and you want to determine when your busiest times of day are. This would come in handy for scheduling drivers. You need more drivers during busy times because no one wants to wait for a taxi!

Read on to see one way to create the table in Power BI.

A couple years ago, I wrote about exploring a running database by plotting relevant subsets of the foreign key relationship graph in dot and piping the resulting images directly to the terminal. Things have progressed since then:

Read on to see what’s changed, including support for displaying trigger relationships.

Concurrency control is an essential aspect of database systems that deals with multiple concurrent transactions. PostgreSQL employs various techniques to ensure concurrent access to the database while maintaining data consistency using atomicity and isolation of ACID (stands for Atomicity, Consistency, Isolation and Durability – https://en.wikipedia.org/wiki/ACID) properties.

The majority of the article focuses on Multi-Version Concurrency Control, which is also the concurrency option which would be least well-known to SQL Server users.

I’ve done a few BI integration projects extracting data from ERPs running on IBM Db2. Most of the implementations would use a hybrid architecture where the ERP would be running on an on-prem mainframe while the data was loaded in Microsoft Azure. Here are a few tips if you’re facing this challenge:

Click through for five major points. Surprisingly, one of them isn’t “Avoid DB/2 like the plague.”

Turning the question around, however, leads you to some aspects of the question that haven’t been fully explored. Instead of asking “Can I run Power BI Desktop on my Mac?”, you can instead ask “Can I do all of my Power BI development using only a browser?”. At Microsoft our long-term goal is to make all Power BI development web-based, but how close are we to that goal?