On Wednesday the 27th, EK’s Holly Maykow, Senior Data Specialist, and Fernando Aguilar, Senior Data Scientist, will deliver a presentation titled Customer 360 and its Applications, a Case Study. This presentation will discuss a case study on how an identity graph represents a comprehensive view of a consumer, giving a global company a 360-degree view of their customers, attributes, and key business insights. Key topics of the talk will include how to define a customer identity graph as well as the requirements for building one. Common challenges and roadblocks to consider before and during identity graph implementation will also be explored.

Also on Wednesday, Joe Hilger, EK COO, will serve as a panelist on the closing presentation of the conference, Delivering and Scaling Knowledge Graph Solutions. Joe will be joined by Robert Engels, VP CTO Europe I&D at Capgemini, Carlos Alberto, Data Protection Officer at Fujitsu, and Vassil Momtchev, CTO of Ontotext. The panelists will cover topics including real world knowledge graph use cases, deployment patterns, and technology ecosystems for graph databases. The session will be moderated by Juan Sequeda of data.world as a special edition of the Catalog and Cocktails podcast.

The virtual conference will provide opportunities to connect with fellow professionals and entrepreneurs, learn from experts across two main tracks, and get an overview of the market and technology trends from industry leaders.

Learn more and register for the forum here.

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Enterprise Knowledge (EK), the world’s largest dedicated knowledge and information management consulting firm, announced the launch of the Knowledge Graph Accelerator today, a mechanism to establish an organization’s first knowledge graph solution in a matter of weeks. In partnership with data.world, the knowledge graph-based enterprise data catalog, organizations will be able to rapidly unlock use cases such as Employee, Product, and Customer 360, Advanced Analytics, and Natural Language Search. 

“Knowledge Graphs are a critical component necessary to achieve Enterprise AI, but most organizations need a quick and scalable way to understand and experience the value,” said Lulit Tesfaye, Practice Lead of Data and Information Management at EK. “EK, in partnership with data.world, is creating a holistic solution to make building Enterprise AI intuitive using knowledge graphs, from data modeling and storage to enrichment and governance. Having this end-to-end consistency is critical for the success of knowledge graph products and setting the foundations for Enterprise AI.”

“EK has been at the leading edge of Knowledge Graph strategy, design, and implementation since our inception,” added Zach Wahl, CEO of EK. “Our thought leadership in this field, combined with data.world’s advanced capabilities, creates an exciting opportunity for organizations to feel the impact and realize the benefits quickly and meaningfully.”

Gartner predicts that graph technologies will be leveraged in over 80% of innovations in data and analytics by 2025, but many organizations find the business and technical complexities of graph design and implementation to be daunting. The Knowledge Graph Accelerator addresses the need to develop a practical, standards-based roadmap and prototype to quickly realize the potential of knowledge graphs. 

Through the Knowledge Graph Accelerator, organizations will get the following outcomes in less than 2 months:

• An understanding of the foundations of knowledge graphs, including graph data modeling, data mapping, and data management;
• A first implementable version (FIV) knowledge graph that can be scaled and enhanced;
• A pilot version of your graph solution leveraging the knowledge graph-based data management solution data.world and gra.fo; and
• A strategy for your organization to make Enterprise AI a reality. 

“Enterprises need to understand and trust the data powering their analytics while generating meaningful insights. But supporting different data sources and use cases, while analyzing and traversing changes to metadata and automating relationships can be challenging,” said Dr. Juan Sequeda, Principal Scientist at data.world. “Knowledge graphs are foundational for an effective and future proof data catalog, as well for next generation AI and analytics .”

To learn more, explore our approach and what your organization will get through the Knowledge Graph Accelerator. Also, reach out to Enterprise Knowledge to learn how to unlock the use cases that are most valuable to your enterprise. 

On September 29th, 2021,  Enterprise Knowledge will participate in the virtual data.world fall summit. Additional keynote speakers include Zhamak Dehghani, Barr Moses, Doug Laney, and Jon Loyens. 

About Enterprise Knowledge 

Enterprise Knowledge (EK) is a services firm that integrates Knowledge Management, Information and Data Management, Information Technology, and Agile Approaches to deliver comprehensive solutions. Our mission is to form true partnerships with our clients, listening and collaborating to create tailored, practical, and results-oriented solutions that enable them to thrive and adapt to changing needs. At the heart of these services, we always focus on working alongside our clients to understand their needs, ensuring we can provide practical and achievable solutions on an iterative, ongoing basis. Visit enterprise-knowledge.com to see how optimizing your knowledge and data management will impact your organization.  

About data.world

data.world is the enterprise data catalog for the modern data stack. Our cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful knowledge graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than 1.3 million members, including 2/3 of the Fortune 500. Our company has 40 patents and has been named one of Austin’s Best Places to Work six years in a row. Follow us on LinkedIn, Twitter, and Facebook, or join us.

The post Enterprise Knowledge and data.world Partner to Make Knowledge Graphs More Accessible to the Enterprise appeared first on Enterprise Knowledge.

The Solution

In order to deduplicate the records and associate them to identifiable, unique individuals, EK’s team of experts started from the bottom up, conducting an exhaustive exploratory data analysis of each attribute in the data. Using the completeness and uniqueness of data fields, we then prioritized fields for further exploration, allowing us to quickly deliver value by focusing on the data attributes with the highest relevance for matching individuals.

Working with our partner, we developed a data processing pipeline to take messy input data and create a graph of linked records that corresponded to real world individuals. Our pipeline focused on the following steps:

• Data Cleaning and Normalization – Our first step involved cleaning and standardizing data to maximize matching opportunities. 
• Graph Construction – To maximize our potential for matching records, we constructed a knowledge graph, allowing us to match records through the graph based on shared attributes or intermediary nodes.
• Rules-Based Matching Algorithms – After looking for explicit matches, EK developed algorithms that would link records pertaining to the same individual.
• Iterative Validation and Match Quality Improvement – Every matching algorithm developed was documented, validated, and adjusted to ensure quality results and alignment with business stakeholders. Furthermore, working in an Agile manner, EK was able to both continually build on existing algorithms and develop new rules, increasing the quantity and quality of matches.

The EK Difference

EK’s vast experience in knowledge graphs played a key role in delivering a transparent, explainable solution that outperformed the client’s existing black box legacy systems. Using an Agile approach, EK was able to maintain alignment with both our partner and the marketing firm’s business stakeholders, ensuring that we were able to deliver high value results quickly. In addition to building state-of-the-art graph models, conducting in depth data analysis, and writing detailed technical reports, our data scientists, graph engineers, and analysts collaborated to ensure that all technical terminology and decisions were documented in a business glossary that was accessible to non-technical users. In doing so, EK was able to leverage our knowledge sharing culture, facilitating discussion and collaboration with key stakeholders to ensure the end solution was a true made-to-measure system that solved our client’s unique business needs.

The Results

By implementing our data pipelines and matching algorithms on the knowledge graph, we managed to reduce the number of unique records by 70% percent, more closely aligning with the target population of 240 million marketable US adults. In doing so, we allowed our client to connect the dots between data that was previously siloed in separate systems, creating a clearer picture of customer behavior and trends. Through collaboration with our technology partner, we continue to fully automate the graph creation and deduplication process. This gives our client the ability to quickly ingest and connect new data, ensuring that the graph, and corresponding business intelligence, will continue to expand.

360-view-of-a-Consumer-Deduplicating-and-Constructing-Consumer-Data-Using-an-Identity-GraphDownload

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