Neo4j Bloom: What’s New with Neo4j's Data Visualization Tool

Editor's Notes

• #2: Jessica welcomes, introduces herself, passes to Jeff to introduce himself and go over the agenda (next slide).
• #3: Jeff Time at the end for questions - if not, feel free to reach out via email or find us after the talk.
• #4: Jeff
• #5: Jeff Of course, at our core we have the Neo4j Database Graph Data Science (Library) works well alongside Neo4j runs everywhere, including in embedded systems and in the cloud, whether self-managed or on our Aura platform (Aura Free, Pro, Enterprise, DS offerings) BI Connectors & drivers Cypher Query Language Developer Tools (Neo4j Browser, GraphQL) Finally, User Tools (Neo4j Bloom)
• #6: Jeff
• #7: Jeff (A:Red) Domain Specialists & Analysts: These users do not generally write queries and rather rely on point-and-click user interfaces and are likely to consume graphs via deep links or shared visualizations. They will typically consume outputs Largest user group No code/low code Experts in their domain (e.g. fraud detection, IT security, supply chain management, customer retention, etc., etc.) (D:Blue) Developers: Or Graph SME (subject matter expert). These folks create the graph database, write Cypher queries and develop applications. They are often the gateway and/or champion to take Neo4j to the business. Looking for a low barrier to entry for graph data visualization to present concepts/findings easily. Important user group, experts in the field of software development Supporting analysts via Saved Cypher or Perspective design, Access controls, Deep links Also may see value in Bloom for exploring/understanding data sets (S:Green) Data Scientists: These users are experts in data. They understand SQL and other data tools and use them often. They may write Cypher queries, although they may not write queries all the time and would prefer using a UI tool. They are responsible for feeding business input into applications and act as liaisons with Enterprise Developers and Domain Specialists. Similar to developers, experts in deriving insights and value from data Supporting analysts/developers via analytic pipelines, predictive analytics, etc. Also may see value in Bloom for exploring/understanding data sets & trying things out before processing larger datasets
• #8: Jeff
• #9: Jessica
• #10: Bloom, is a powerful graph visualization tool and as Jeff mentioned, Bloom aims to be be intuitive, reliable and useful to a variety of users, regardless of coding background. It has six main components. In brief: Perspective - define a certain business view or domain within your graph that should be available for exploration. We will have a closer look at Perspectives shortly. Visualization - The main idea of Bloom is to let you actually see the nodes and relationships in your data. Bloom offers GPU accelerated visualization with high performance physics and rendering to do so. Exploration - Bloom lets you interact directly with your graph using your mouse, what you see is not necessarily what you get. You can select elements, expand them or dismiss them or find paths between them, among other things. Inspection - any visible element can be inspected for its details. You can find its properties, relationships and neighbors, to name a few things. Editing - if you have write access to the graph, you can actually make changes to the graph. You can create new elements, edit and delete existing elements without using any code at all. Search - Explore your data through graph patterns. No code required, but Cypher can be used in custom search phrases and scene actions. More on that later on.
• #11: Jessica Background notes in case of questions (which Jeff can field if needed): As I mentioned previously, a Perspective lets you control which elements from your graph should be available for exploration. If you don’t want all of your data, you can decide to include or exclude both node categories as well as relationship types and their properties to fully customize the Perspective to suit your needs. You can also customize the default styling, ie colors, sizes, icons of available elements in your Perspective. Additionally, a Perspective can be based on saved Cypher, which is either a Search Phrase or a Scene Action. These will be explored in greater depth later, but in brief, they are custom Cypher statements that apply either to all data or selected data in your scene. Autoperspective First use of Bloom Basic on a new DB Fully automatic Completely user-transparent Generate Perspective Option from the Gallery Semi-automatic Blank Perspective Option from the Gallery Create your perspective from scratch In all cases, as data is added to the scene, Bloom becomes aware of additional properties
• #12: Jessica Let’s have a look at the UI of Bloom. I’m not going to go over every feature here, just shine some light on on some of them. The scene - contains the graph elements returned from your search or other actions such as expand. Perspective drawer - this is where you define your Perspective, as discussed in the previous slide Settings drawer - this drawer contains various options for the application, from node query limit to property tooltips and case sensitivity and suggestions in the search bar Card list - when you expand this, you can see information about all elements in your scene. You can filter the returned cards by either typing something in the search bar in the card list or by selecting either nodes or relationships. You can also see the details of any individual element. Legend panel - this is where you can style the elements of your scene, including which captions should be visible for nodes and relationships. You can apply rule-based styling, ie change the colors and sizes of both nodes and relationships based on a rule you specify. Layouts - hierarchical vs physics layout Export - if you find an interesting scene, you can export it as a screenshot or as csv files.
• #13: Jessica Bloom Full Access requires a plugin and is currently only available for Self-managed customers. Aura Enterprise customers should stay tuned for pilot opportunities in future. Sharing and Authorization: With Full Access, you can share perspectives and scenes to Neo4j roles. With Basic, perspectives can only be shared by exporting and re-importing them into a local client. Fine-grained access controls in Enterprise databases will still be respected by both Basic and Full versions of Bloom, however.
• #14: Jeff will introduce section and start with 1.7 -It’s been a busy year and we’ll take a lightning speed walk through a number of new features and enhancements we’ve made along the way -Shout-outs to key features that will be explained in detail next. -We have a two month release cycle, and will walk through the last six releases. Jeff & Jessica will alternate through the different Bloom versions in the section.
• #15: Jeff
• #16: Jeff Initial date/time support enabled editing on non-timezone components of Neo4j date/time types, but did not enable filtering or rule-based styling for timezoned types.
• #17: Jessica Tooltips - When you hover over a node or relationship, you’ll see a tooltip containing certain captions. You can customize these in the legend panel. Reveal relationships - you can select two or more nodes and see if there is any relationships between them directly from the context menu. SSO - unlike the previous version of Bloom, which only included custom SSO solution, in Bloom 1.9 we started offering support for SSO in Neo4j 4.4
• #18: Jessica Scene saving and sharing - Much like how you sometimes need multiple tabs in your browser or multiple windows, you may need multiple scenes in Bloom to achieve your objective. You can save your current scene to perhaps start fresh in a new scene. Your saved scene remains the same when you return to it. You can also share your scenes with other users of the same database. This is done by selecting which roles you want to share with. This is an Enterprise feature. Histograms - These are available to help you set values for both rule-based styling and for filters based on the values available in your scene. Editing Enhancements - In 2.0, you can create nodes even if the node’s label has constraints, such as uniqueness for a certain property, for example. Bloom prompts you to add this property when creating a new node of said label. Additionally, you can also add properties to existing nodes as well as delete both nodes and relationships. Any editing requires write access to the graph, of course.
• #19: Jeff
• #20: Jeff
• #21: Jeff
• #22: Jeff E-SR4
• #23: Developers/power users can help analysts Can define dynamic suggestions
• #26: Captions can now be configured for Relationships as well as Nodes. Can find captions in the ‘Text’ tab of the styling pane via the Legend. Also able to create Rule-based styling with text.
• #28: Will also be a Basic Access feature available to everyone (requires GDS plugin)
• #29: Jessica To summarize, today we’ve seen where Bloom fits into the Neo4j ecosystem of products and who its main users are. We walked through an overview of Bloom and had a closer look at Perspectives and the UI and learned some differences between basic and full access to Bloom. We’ve seen some highlights from the releases over the past year, it’s been an feature-packed year! Then Jeff walked us through some of the most important and widely anticipated of these features and we got a preview of the exciting GDS integration in Bloom, which will be available in the upcoming release, due next week.
• #30: Jessica
• #31: Jessica We believe the slides will be available after the conference, if not, feel free to get in touch with us and we’ll share the links.
• #32: If we have time, Q&A