GraphNews

At eBay, we are obsessed with data quality and governance. Because eBay's Hadoop platform hosts 500 PB of data running over 15,000 nodes, the focus on governance is of utmost importance. This article discusses our experiences handling data governance at scale.

Learn the fundamental algorithms and theories used for understanding large-scale graphs and knowledge graphs.

So many options in fast moving the graph database world, which one should you choose?

As of late Q2 of 2018, there’s a new entry into the graph database marketplace, Amazon Neptune.

Graph machine learning finds dissatisfied customer cohorts an recommends optimal intervention measures.

Follow these tips to speed up your JanusGraph queries when running against a variety of storage backends including Apache Cassandra, ScyllaDB, Apache HBase, and Google Cloud Bigtable.

Neo4j, DataStax Graph and Janus property graph schema design decisions for vertex and edge definitions.

Your business has its own language. If you sell cars, then you need not only make, model and year, but also MSRP, leather bucket seats and dealer incentives. Media companies have producers and writers, actors and grips, distribution networks and video masters. Business Language

You may have also noticed the emergence of 360° initiatives, letting you see how all the data within your organization relates to other data, and that it should also be possible to dig deep into your data systems to power natural language chatbots, dashboards, data analytics, and more

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

With the rapid rise of graph technology, it's time for a standard language for querying graphs. That work is already underway.

GDPR can offer valuable insights into your organization's overall visibility.

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AI is in its infancy and cannot be left unattended. Whether unintentional or by malicious design, algorithms behaving unexpectedly are now a fact of life.

An evaluator's task is to connect the dots between program goals and its outcomes. This can be accomplished through surveys, research, and interviews, and is frequently performed post hoc. Research evaluation is hampered by a lack of data that clearly connect a research program with its outcomes and, in particular, by ambiguity about who has participated in the program and what contributions they have made. Manually making these connections is very labor-intensive, and algorithmic matching introduces errors and assumptions that can distort results. In this paper, we discuss the use of ident...

Multi-model Azure database combines global reach and a choice of five consistency models, allowing you to trade off cost for consistency

How TigerGraph achieves fast data ingest, fast graph traversal, and deep link analytics even for large data sets

How TigerGraph achieves fast data ingest, fast graph traversal, and deep link analytics even for large data sets

For those juicy technical details, hop over to our technical documentation. For a more newsy take, you can read our press release here.

Bye Bye Silos! Those who stay on their islands will fall back. This statement is valid on nearly any level of our increasingly complex society, ranging from whole cultural areas down to single individuals.

Last week I attended the International Semantic Web Conference (ISWC) in Monterey, CA. My role was to speak at the Ada Lovelace Day Celebration about the work that Elsevier is doing with regards to measuring and fixing the gender gap in research (see more here).

New MarkLogic Data Hub Service delivers both agile data integration and agile data infrastructure—with unmatched security and governance, and predictable costs.

Thu, Sep 25, 2014, 6:30 PM: Our Topic This MonthGraphs are a perfect solution to organize information and to determine the relatedness of content, such as the connection between phrases and words in t

Titan, Tinkerpop, Neo4j, ArrangoDB, OrientDB, but I still have a fondness for grep/sed/awk and flatfiles.

We’re bringing new experiences to Microsoft Search into the apps you use every day.

Earlier this year, we were fortunate enough to be contacted by Brian Keegan, Assistant Professor in Information Science at the University of Colorado Boulder, who specialises in the field of network analysis. Brian and his team were planning to mine the official biographies of every legislator pu

Machine learning algorithms don’t yet understand things the way humans do — with sometimes disastrous consequences.

The O’Reilly Data Show Podcast: Fabian Yamaguchi on the potential of using large-scale analytics on graph representations of code.

For a presentation at the Neo4j User Meeting in Tokyo I have converted the TeX Live Database into a Graph Database and represented dependencies between all kind of packages as well as files and their respective packages as nodes and relations. Update 20181010: I have worked out the first step…