Loading Data using R and PowerBI
I'm not a fan of R visuals in PowerBI. I recently learned I can use R to load data and native PowerBI visuals to display the data. Here's how.
2022-05-27 (first published: 2017-10-16)
6,925 reads
Nick Burns
Pattern Recognition via Principal Components Analysis
We'll look at using principal components analysis to help visualise your data and detect underlying structure or patterns.
2019-10-25 (first published: 2017-09-12)
10,312 reads
Moving beyond principal components analysis
Principal components analysis is a standard, but usually terrible, technique for visualising complex data. We're using network diagrams to solve this problem.
2019-10-11 (first published: 2017-09-19)
2,555 reads
Real-time moving averages for IoT with R
Computing an average over all your data is easy, but what if your data arrives incrementally and you need to be able to compute real-time averages on the fly? That's what we are going to look at.
2019-10-04 (first published: 2017-10-02)
2,976 reads
Configuring R Services in SQL Server 2016
R Services provides in-database analytics in SQL Server 2016. In this article we step through configuring R Services and get you started with in-database analytics.
2018-05-28 (first published: 2016-01-27)
4,876 reads
The Shortcomings of Predictive Accuracy
In prediction, accuracy is key. But it's not all it's cracked up to be as we will explore.
2017-09-07
1,265 reads
Analysing Sales Patterns: R + SQL Server
We show how to use RevolutionR to analyse & visualise purchasing behaviours in AdventureWorksDW2012.
2017-08-18 (first published: 2015-12-15)
7,947 reads
Machine Learning for Outlier Detection in R
A look into clustering to detect outliers in R. An extension on univariate statistical tests to include multivariate data.
2017-07-05
3,857 reads
Scoring Outliers in Non-Normal Data with R
Using R to detect outliers is relatively easy, but most methods assume your data is normally distributed. How do you handle skewed datasets?
2017-06-29
5,534 reads
Scoring Outliers with R
What is normal? More to the point, what is abnormal? We will look at using R to score outliers in a typical monitoring dataset.
2017-06-19
4,063 reads
Blogs
Slide Decks
Hello everyone! Just a quick note. I’ve removed all my slide decks from SlideShare....
Deploying SQL Server to Kubernetes via SQL Server 2025
Following on from my previous post about hitting the Kubernetes API from SQL Server...
Step-by-Step SQL Server Migration Using SSMS: Best Practices & Use Cases
By Rohit Garg
Introduction Migrating databases can be a complex task, especially when dealing with large-scale systems...
Forums
One of two secondary replias is stuck in restoring
Good afternoon, I had a 7.8 TB database that needed some work. I removed...
Model Context Protocol (MCP): A Developer’s Guide to Long-Context LLM Integration
Comments posted to this topic are about the item Model Context Protocol (MCP): A...
Question of the Day
Capacity Planning for an Existing SQL Server Workload?
You're tasked with planning capacity for a new SQL Server database workload. Which of the following is the most accurate way to determine how much CPU, memory, and I/O throughput your workload requires? What single or multiple tools would you use to answer the questions around resource needs?
See possible answers