A recap of CDW21, plus announcing our first in-person Meetup in over 2 years, and the first book on Personal Knowledge Graphs! Are you a runner, or a professional? That's not an either/or question, of course - nothing says you can't be both, and that's the case for us here in Connected Data World! Even if you're neither, however, you're probably familiar with the notion of sprints.
In Agile project management, Sprints refer to short, repeating blocks of time in which key parts of the project are completed. In sports, sprinting is running over a short distance at the top-most speed of the body in a limited period of time. Either way, after a few sprints, some rest to recuperate is in order.
Connected Data World 2021 felt like a marathon ran sprinting the whole way through, and we did need some time to recuperate. But we're up and running again, and we have some news for you. Join us for a recap of CDW21, our first in-person Meetup in over 2 years, and the first book on Personal Knowledge Graphs!
CDW21: Our biggest virtual event ever, as real as it gets
First off, we owe a big thanks to everyone who helped make Connected Data World 2021 a success: speakers who shared their knowledge with the world, sponsors who supported the event and made organizing it possible, and of course everyone who attended.
With more that 80 speakers and 50 sessions, from the likes of Bloomberg, BMW, Elsevier, IKEA, Intel, LinkedIn, Microsoft, Siemens Energy and Wells Fargo, it was our richest lineup ever. Our sponsor lineup, both new returning ones, was also amazing:
TigerGraph and Katana Graph were our Platinum sponsors, EnterpriseWeb (who also sponsored our Presentation Day), ArangoDB, TerminusX, Oxford Semantic Technologies, Ontotext, BlackSwan Technologies, Amazon Neptune were our Gold sponsors, and Fluree was our Bronze sponsor.
Of course, all that would not mean much without an audience to share it with. With close to 1.500 registrations, shared among our different access passes (Free, Diversity & Inclusion, Full), we like to think we provided everyone the opportunity to learn, share and network.
CDW21 was a virtual event, following in the footsteps of Knowledge Connexions, but as you've told us, it was unlike any other virtual event you've been to.
Imagine an event where you can walk about, bump into old acquaintances and strike up conversations with new connections, take your place to attend talks, ask questions directly, give a round of applause, gather up and hang out at the lounges, and even have drinks and dance to the music at the after party.
That's as close to the real thing as it gets - if you were there, you know! If not, well, you missed out on a lot of fun - but fret not. All the Presentations, Workshops and Masterclasses are there for you to watch and learn from. You can still grab your pass and watch at your own pace.
Connected Data London Meetups are back: Graph-based Stream Processing with Python
Of course, there's nothing like the real thing. We really missed interaction in the real world, and we're pretty sure you did too. Good news: After a long, COVID-induced hiatus Connected Data London Meetups are back!
On April 27 at the Edinburgh House in London, we have Memgraph visiting from Croatia who will give a fascinating talk on Graph-based Stream Processing with Python. Seats are limited, so make sure you secure yours.
The understanding of complex relationships and interdependencies between different data points is crucial to many decision-making processes. Fraud detection, recommendation engines, and process optimization are some of the use cases where real-time decisions are mission-critical, and the underlying domain can be easily modeled as a graph.
Graph analytics can provide insights into complex networks that would otherwise require resource-intensive computations. It is also much simpler to store streaming data in the form of graphs, as the graph model doesn't rely on predefined and rigid tables.
By ingesting data with Apache Kafka and applying graph-based stream processing in real-time, you can perform near-instantaneous graph analytics on vast amounts of data. When connecting a Kafka data stream to Memgraph, you only need to create a transformation module that will map incoming messages to the property graph model.
Join Ivan Despot and Katarina Šupe as they show and tell how it all works with Memgraph, an open-source streaming platform that can be used to analyze graph-based data models. Doors open at 6.30pm and the talks start at 7. As usual attendance is free, and refreshments and pizza will be available courtesy of our sponsors Memgraph & Neural Alpha.
The first Personal Knowledge Graph book: Call for Submissions
Knowledge graphs are a universal and flexible data abstraction, and a way to see the world as a network of meaningful connections. From Google to Airbnb and Netflix. From DBpedia to Wikidata and UniProt. A vibrant community is shaping around knowledge graphs, and thought leaders in enterprise data management are endorsing related initiatives and principles.
But what does that all mean to each of us, in terms of our own work and our daily lives? Could knowledge graphs be relevant on that level?
A new generation of tools aiming to democratize access to knowledge management best practices and technology previously reserved for professional use is on the rise. After open and enterprise graphs, we see an increasing number of people managing their personal data as knowledge graphs.
After organizing a working group on Personal Knowledge Graphs and a Workshop on the topic in CDW21, our own George Anadiotis is joined by PKG connoisseur Ivo Velitchkov as they announce the first Personal Knowledge Graph book: Call for Submissions.
If you work with Personal Knowledge Graphs, consider submitting a chapter to the first PKG book which is a graph itself by May 1 2022. And be sure to follow the PKG Book on Twitter and LinkedIn for updates!
Comments