Cypher, a query language designed specifically for graphs, allows for expressing complex graph patterns using simple ASCII art-like notation and offers a simple but expressive approach for working with graph data. In this on-demand webinar we explore a data set using Neo4j and Cypher and compare the approach we might take with a relational database and SQL. 

Maria Scharin
Neo4j Engineer

Maria is part of Neo4j's Engineering team based in Malmö. She holds an MSc in Engineering from Lund University, and has an extensive technical background as a developer, Oracle DBA and IT project manager. Her passion lies with communication and beautiful language. She gets a kick out of explaining complicated things in a simple way, which is the perfect match for making Neo4j accessible for all sorts of audiences. Maria is married and has two kids. In her free time, she enjoys long-distance running and yoga, reading, and spending time with her family.
Andrew Chumney
Single View Solutions Manager, Pitney Bowes

Andrew Chumney joined Pitney Bowes in May 2017 after a 20-year consulting career where he provided executive leadership in corporate restructuring, turn-around, mergers and acquisitions. His particular area of focus was operational efficiency, business intelligence, large enterprise master data management, technology architecture, marketing and brand development. His major clients have included Department of Defense, DynCorp, Lockheed, U.S. Department of Veterans Affairs, Verizon, ABC Radio Networks, Boeing (Jeppesen), Kaiser Permanente, IHS, Owens & Minor and PetSmart.

Most recently his projects have been focused on data science, data patterns and large enterprise master data management architectures. Andrew’s background in large system development and consulting projects allows him to bring a deep understanding of best practices and methodologies from a broad spectrum of vertical markets; manufacturing, healthcare, telecommunications, professional services and defense related industries.

Kelsey Bieri
Data Governance Analyst, ICC

Kelsey Bieri is a Data Governance Analyst at ICC in the Master Data Management and Data Governance Practice. She has contributed to numerous data governance and data lineage projects in the Banking industry, helping organizations build a better understanding of their data universe. Kelsey holds a degree in Management Information Systems from the College of Business at Ohio University.