Just over a year ago Kenny Bastani wrote a blog post showing how to analyse GitHub Events using Apache Pinot and Kafka. In this blog post, we will build on Kenny’s work, but instead of using Apache Superset to visualise the data, we’ll be using a Python library called Streamlit.
The code used in this blog post is available in the mneedham/pinot-github-events repository if you want to follow along or try it out afterwards:
To recap, Apache Pinot is a data store that’s optimised for user-facing analytical workloads. It’s good at running real-time queries on event data.
We’re going to…
I recently started working at a London FinTech company called Finbourne who make a cloud-based data platform for investment data called LUSID.
It’s mostly used by hedge funds, pension companies, and investment banks to store their trading data, but you can use it to store your own personal investment data as well.
My colleague Mike McGarry has done exactly this, importing data from his personal financial accounts and investments, and then using LUSID to compute his net worth over time.
Reading Mike’s blog posts got me wondering if we could use LUSID to build a portfolio of holdings in different…
In the world of Covid data, Thursday afternoons are my favourite because that’s when NHS England publish their weekly vaccinations spreadsheet.
In this blog post, we’re going to explore the data published in the spreadsheet to learn how the vaccine rollout is going in different parts of the country.
The spreadsheet contains data on the number of vaccinations given by age group and by region, as well as population estimates for each of these areas.
The data is a few days behind the aggregate data shown on the official dashboard, so we need to keep that in mind when doing…
NEuler (Neo4j Euler) is a UI that simplifies the onboarding process for users of Neo4j’s Graph Data Science Library (GDSL). It was first released in early 2019 when it was used to onboard users of GDSL’s predecessor, the Graph Algorithms Library.
Over the last few months, we’ve made changes, which will (hopefully!) make it easier to use and get you up to speed quicker with GDSL.
The NEuler Developer Guide contains instructions for installing the app or you can watch the video below.
Let’s have a look at what changes have been made.
One usability problem that many…
Its successor, the Graph Data Science Library, was recently released, which meant that NEuler needed to be updated to use that instead.
I’m happy to announce that as of version 0.1.16, NEuler is Graph Data Science Library ready. It has also been renamed to be the Graph Data Science Playground!
This version is only supported by Neo4j Desktop versions 1.2.5 and higher, so you’ll need to update that as well.
If you had…
So we’ve been using Neo4j via Neo4j Desktop for a while now, building up a formidable collection of databases, and then a few weeks ago we learned about the launch of this thing called Neo4j Aura.
Neo4j Aura is the simplest way to run Neo4j in the cloud. Completely automated and fully-managed, Neo4j Aura delivers the world’s most flexible, reliable and developer-friendly graph database as a service. With Neo4j Aura, you leave the day-to-day management of your database to the same engineers who built Neo4j, freeing you to focus on building rich graph-powered applications.
This week we released version 184.108.40.206 of APOC, Neo4j’s standard library.
This release contains the following features and bug fixes:
apoc.coll.containsAlland Mongo procedure
apoc.periodic.repeathas improved reporting for bad queries
apoc.graph.fromDocumentconsiders whitelist property mappings
You can install the latest release directly from the Neo4j Desktop in the ‘Plugins’ section of your project. Jennifer Reif also has a detailed post explaining how to install plugins if you haven’t used any yet.
Over the last month or so we’ve released new functionality for the Neo4j Graph Algorithms Library, in versions 220.127.116.11, 18.104.22.168 and 22.214.171.124.
These releases see the following features and bug fixes:
Note that this release is only compatible with Neo4j 3.5.9 and above. You can read more about the release in the release notes.
ANN leverages similarity algorithms to efficiently find more alike items. In this post, we’ll look at our motivation for creating this algorithm, where it can be used, and will show how to use it with the help of a worked example.
It’s now been almost a year since we added similarity algorithms to the Neo4j Graph Algorithms…
A month ago I wrote a blog post about a Neo4j graph I’d created containing all the football transfers in the Summer 2019 Window.
While I was able to explore the data easily using Cypher queries, I wanted to make life a bit easier for myself by putting a front end around the data.
It seemed like a good opportunity to create my first GRANDstack application, which is exactly what I did.
I started by creating a new repository based on the GRANDstack starter kit GitHub template. We can find that template at github.com/grand-stack/grand-stack-starter: