Senzing

Entity resolution is critical to creating an accurate knowledge graph. Here is a step-by-step tutorial using Neo4j and Senzing. Entity resolution is the process of identifying and connecting data that refers to the same real-world entity. While it often includes de-duplication, that comes after the entities are identified and connected. There are many ways to perform entity resolution, but graphs are particularly well suited to this task. Additional tools including Neo4j's Graph Data Science library and third-party tools like Senzing can make the task faster and more efficient. Recently Paco Nathan from Derwen AI published an entity resolution tutorial on the Neo4j Developer blog. This is an extensive, step-by-step approach to applying entity resolution to business data including Paycheck Protection Loan (PPP) data. I started my career as a forensic accountant and the Panama Paper's was my catalyst to move into data science, so the PPP loan data is certainly close to my heart. Paco does a great job including example code and very clear steps, so this is a great tutorial to keep bookmarked. I know that I plan to. You can find the full, in-depth tutorial here: https://lnkd.in/g8U3MjiW Entity resolution is a key step to many graph use cases including fraud, Customer360, and recommender systems. Even if you are not working with fraud, it is a powerful approach to know. Follow me Daniel Bukowski for daily posts about the intersection of graphs, data science, and GenAI. #neo4j #senzing #entityresolution

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📣 This might be one of the biggest and most important live broadcasts in LinkedIn history! No sign up required but please register to receive notifications and save the event to your calendar so you don't miss it!

Could this be the biggest LinkedIn live broadcast, ever? We've asked these elite data leaders to 'weigh-in' on whether or not business leaders should increase their investments to support data maturity. Elite Speakers 1️⃣ ⭐⭐SCOTT TAYLOR⭐⭐ The Data Whisperer | Data Storytelling | Data Puppets | DataVengers | Keynoter | Brand Content | Event MC/Host | DataIQ100 | Onalytica Who’s Who | CDOMag Top Consultant | 5X Data Marathon Host | Dataversity Top10 Blogger 2️⃣ ⭐⭐Bill Schmarzo⭐⭐ The Dean of Big Data, CDO Chief AI Officer Whisperer, recognized global innovator, educator, and practitioner in Big Data, Data Science, & Design Thinking 3️⃣ ⭐⭐Jeff Jonas⭐⭐ CEO, Founder, and Chief Data Scientist at Senzing, Former IBM Fellow 4️⃣ ⭐⭐Nathan A Cunningham ⭐⭐ Founder of WIPP Data, Fractional Data Science and Analytics for Supply Chain Teams 5️⃣ ⭐⭐Henrik Gabs Liliendahl⭐⭐ Data Management Veteran, Founder @ The Disruptive MDM / PIM / DQM List, Co-founder @ Product Data Lake 6️⃣ ⭐⭐Shireen Abedin⭐⭐ Founder, Lead Data Scientist, Abedin Analytics 7️⃣ ⭐⭐Tris J Burns 🔥⭐⭐ Data Leadership Coach & Advisor | International Keynote Speaker | Former Global Head of Data at Pizza Hut Digital | Former Analyst at Bank of America Merrill Lynch 8️⃣ ⭐⭐Samir Sharma⭐⭐ CEO at datazuum | Data & AI Strategy Leader | Target Operating Models Expert | Speaker | Host of The Data Strategy Show This event will be hosted by Ben C., The Data Matching Pro, Co-Founder at Match Data Pro, and Angeline Corvaglia, Founder of Data Girl and Friends. What do we mean by data maturity? The ability to understand, manage, and improve upon an organizations' operations and outcomes. Most organizations cannot do any of this without some form of data. Be it something as simple as sales and bookkeeping data or a larger and more sophisticated company with investments in quality, governance, MDM and predictive analytics. Maturity refers to a 'development' process. This is an investment in the talent, time, learning, organization, support, budget, infrastructure, and other things necessary. We're broadcasting live from the Match Data Pro page on LinkedIn on July 17th at 11am US Central time. Hope to see you there! It's an ungated event so please go register for the event to receive a reminder, and block off some time on your calendar.