As organizations undergo digital transformation to analyze and query large amounts of data at high speeds, they are increasingly leveraging graph databases to illuminate information about connections.
The result is that 2018 will be the year of the graph, said Sean Martin, CTO of Cambridge Semantics, during his presentation at Data Summit 2018 titled “The Rise of Graph Databases: From Thomson Reuters to Amazon Neptune.” And, if not just one year, then perhaps we are in the decade of the graph starting with last year, he added.
According to Martin, the recent announcements of Thomson Reuters and Amazon Neptune providing knowledge graphs to their customers serve to validate the effectiveness of using graph-based information as opposed to traditional databases to derive insights and business value.
Martin looked at why Thomson Reuters and Amazon Neptune have turned to graph databases as disruptive and necessary technologies. He also explained how companies in data-intensive industries can use graph-based technologies as a new marketing strategy to maintain existing customers and attract new ones. Graph databases are all about relationships and, with graph technology, you can see how things relate to one another. It also allows data to be structured more naturally he said.
Contributing to graph technology uptake now is that it is becoming mature; there are use cases in areas such as financial services, healthcare, pharmaceutical, and oil and gas; it is being used beyond classical graph technology problems; and the ecosystem is growing.
Scott Heath, CRO, Expero, also reflected on the growing use of graph technology in a presentation titled “Reversing and Querying Complex Graph Data in Real Time.”
Expero has deep domain skills in solving complex problems in a number of fields and frequently partners with graph technology providers, such as DataStax.
According to Heath, DataStax Enterprise (DSE) Graph, coupled with Expero’s expertise in graph and analytics, empowers users to explore and visualize complex graph data in innovative and meaningful ways.
Traditional relational database and other NoSQL systems are not suited for many use cases because the technologies are primarily focused on the entities as opposed to the relationships. This is where graph databases are handy. They make it easy to discover, explore, and make sense of complex relationships. By leveraging the insights in data relationships you can deliver more relevant, real-time experiences for your customers, proactively fight fraud, and ensure the health and seamless operations of your network, he said.
While gaining in popularity now, graphs are not new and have been around since the 1700s, said Heath, who cited Leonhard Euler, a Swiss mathematician, physicist, astronomer, logician and engineer, who made discoveries in many branches of mathematics, such as infinitesimal calculus and graph theory.
Graphs are particularly well-suited for environments where the connections between data points are just as important as the data points themselves, for Customer 360, fraud, supply chain, personalization, recommendations, similarity, path intervention, loyalty/sentiment, allowing for upsell/cross sell opportunities, and showing connections such as phone calls, emails, memberships, and friendships.
Data Summit 2019, presented by DBTA and Big Data Quarterly, is tentatively scheduled for May 21-22, 2019, at the Hyatt Regency Boston with pre-conference workshops on May 20.
Many presentations from Data Summit 2018 have been made available for review at www.dbta.com/DataSummit/2018/Presentations.aspx.