Graph data science: What you need to know

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Whether you're genuinely interested in getting insights and solving problems using data, or just attracted by what has been called "the most promising career" by LinkedIn and the "best job in America" by Glassdoor, chances are you're familiar with data science. As we've elaborated previously, graphs are a universal data structure with manifestations that span a wide spectrum: from analytics to databases, and from knowledge management to data science, machine learning and even hardware. Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points -- that's the 30-second explanation, according to Alicia Frame. Frame is the senior director of product management for data science at Neo4j, a leading graph database vendor.