The post title is boring, but the changes will be less boring.
Seriously, we think you're going to really like the upcoming changes to the Graph Story console. You will almost assuredly tell your friends. Maybe even your family. That dude that you haven't seen since high school, well, that's your call.
One new feature we're really excited about is upgrading your graph (increasing memory, storage, cpu) will become a zero impact, diy operation. It'll be initially offered as "click-to-scale-up" your instances, but eventually you'll have preference settings to auto-scale your instances!
Dan Woods - who covers new technology and written numerous articles on graphs for Forbes - offers his insight into how graph usage can be introduced and grown within organizations. The article is not a deep dive on graphs, but does provide some process and tips for those charged with looking for ways to help drive adoption.
Here's one nugget o' wisdom to be practiced every time you're looking at expanding your graph usage:
Remember that graphs almost always are connected to a person in some way. Follow the money to people. Seek to understand the network surrounding each person. Graph use cases will emerge.
Andreas Kollegger from Neo4j provides an overview using graphs as part of your search platform. Andreas post covers benefits to using graphs in search as well as a few, key challenges.
We see one of the big benefits is the ability to integrate search results activity - such as user searches and resulting clicks - back into collaborative filter (CF) type graphs found in recommendation engines. From the article:
In essence, graph-based search is intelligent: You can ask much more precise and useful questions and get back the most relevant and meaningful information, whereas traditional keyword-based search delivers results that are more random, diluted and low-quality.
With graph-based search, you can easily query all of your connected data in real time, then focus on the answers provided and launch new real-time searches prompted by the insights you’ve discovered.
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Found other awesome resources for graph databases? Let us know!
Until next time (which is about two weeks from now),