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How Neo4j Makes The Hiring Process Smooth

How Neo4j Makes The Hiring Process Smooth

  • Neo4j is a popular graph database management system developed by Neo4j Inc.
Neo4j

Hiring the right talent is one of the biggest challenges for organisations. As per the US Department of Labour, the cost of a bad hire is tantamount to up to 30 percent of an employee’s first-year earnings. HR executives often have to go through endless CVs to make a single hiring decision. The process is time-consuming and the information gathered is still limited in most cases. Even when all the data is available with the recruiter, making sense of it is another ball game.

Of late, companies have turned to technology for recruiting. HR executives especially benefit from graph databases and graph knowledge.

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Neo4j and recruitment

Neo4j is a popular graph database management system developed by Neo4j Inc. Traditionally, large amounts of data don’t render to easy accessibility or analysis. Relational databases could only solve the problem partially: While they deliver plenty of information about individual records in a basic siloed form, they are not designed to show relationship patterns between these records. This is where graph database technology like Neo4j steps in.

Neo4j is an open-source ACID (atomicity, consistency, isolation, durability)-compliant transactional database with native graph storage and processing. While it is implemented in Java, Neo4j can also be accessed from software written in other languages. In addition, Neo4j has high-availability clustering for enterprise deployments. It also comes with a web-based administration which includes full transaction support and visual node-link explorer.

Neo4j efficiently models complex networks of entities and their relationships. Businesses need clear structures to manage reporting processes, role allocation, and authorisations. Neo4j offers an overview of complex organisational charts and a flexible framework, making it easier to find information about an employee, their work, their skill sets across different projects and programs, and also whether they can switch careers in case of skill gaps.

Neo4j can deal with relationship-based queries swiftly, compared to traditional methods. 

NASA’s hiring

NASA is using Neo4j technology to build a knowledge graph to show relationships between people, skills, and projects. As part of NASA’s Future of Work initiative, it has created an internal talent marketplace to expand the understanding of and access to talent from across the businesses to optimise its staffing of different programs. NASA has expanded the scope of recruitment to include factors such as relationships between individuals in the world of work, associated skills and the training required.

Currently, NASA is implementing a Neo4j based project to formalise the end-user application and create an interface for finding talent and job opportunities.

Using knowledge graphs and graph databases makes it easier to add and remove information compared to relational database systems, said David Meza, ang branch chief of people analytics and senior data scientist at NASA, in an interview.

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NASA is one of the many high-profile users of the Neo4j technology. Lyft, ICIJ, and ATPCO also use the tech.

Use cases

Neo4j knowledge graphs have been instrumental in bringing visibility to data, processes, products, and customers. This helps users in seeing the bigger picture and make informed decisions. A Neo4j native graph database provides an intuitive representation of real-world complexity while capturing contextual information and unifying fragmented data.

Neo4j was used by ICIJ (International Consortium of Investigative Journalists) for a global investigative project called the FinCEN Files. Neo4j and ICIJ have been in collaboration since the 2016 Panama Papers investigation which led to the recouping of $1.2 billion in tax revenue across 22 countries.

Lyft also uses Neo4j. Up to 90 percent of Lyft data scientists use Amundsen, a data discovery and metadata engine based on Neo4j. This has helped the company increase productivity by 30 percent.

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