What is Entity Quality?
Most organizations are concerned with data quality. What's usually neglected is the Entity Quality. But what exactly is Entity Quality? Entity Quality, or EQ for short, is a way to determine the quality of a resolved entity. Say we get a resolved entity based on matching 3 different records, based on some matching logic. The question that arises here is: do these 3 records actually represent the same real-world thing/entity? How confident are we that they do? Entity Quality is about that. It's a way to give end users confidence, via a calculated/aggregated score. At Quantexa, we provide Entity Quality Scoring, or EQS, a way to provide confidence scores for resolved entities. It determines over/under linking in entities. Check out a nice short blog on the entity quality overlinking tool that has been developed based on this functionality. That said, this functionality is embedded in the product, and users can view the generated scores easily, and investigate any entity (if/when needed). Do you measure entity quality at your organization? If yes, how? If no, do you think this can be useful? Please share your thoughts!
Elevating Data Management: Unveiling the Pillars of a Trusted Data Foundation with Quantexa
Hi Community! We are all well aware that data teams are faced with increasingly complex business challenges and not being able to make the most of their data makes it very hard to reach strategic, tactical and operational goals set by their organizations. The solution to that is building a truly trusted data foundation. As part of Quantexa’s ongoing commitment to providing best-in-class Data Management solutions to address the latter, the team at Quantexa has had a brainstorm of what aspects are crucial when choosing one, and what we – as a team – are focusing on when building our solutions. Let’s go through some of the main components. 1. Quick multi-source data ingestion: A common challenge is the complexity and time required to get data in the platform. To address that, we apply intelligent data cleansing and enrichment processes and accelerate data onboarding with low-code, schema-agnostic, scalable, high-performance data preparation and ingestion for both internal and external data sources. 2. Truly accurate data matching through Entity Resolution: Without a holistic view of your data, it’s impossible to make informed decisions. Our AI-powered Entity Resolution uses transparent and tunable models that are designed to address common problems associated with traditional matching methods such as data availability and quality issues with proven 99% accuracy. 3. Quality scoring and corrections: Even with the best matching engines, there is always going to be a need for a Data steward’s input: monitoring and continuous data quality enhancement. We provide tools to review the quality score of each entity down to understanding exactly what contributed to a score, quickly identifying source system issues to address. There is also an easy way to correct the data, e.g. merge entities, without needing to adjust the source data, which is incredibly valuable both for immediate use in your analytics and also for any consuming system. 4. The use of Graph Analytics: Connecting data in a meaningful way is a crucial, but the next step is to really uncover the relationships you need for the business problem you are solving. For that our users are able to use advanced Graph Analytics technology to uncover the intricate networks of real-world connections and relationships between entities – building even complex corporate hierarchies or family relationships. Take a look at our video, where , Solutions Lead, shows examples of these capabilities in the Quantexa platform. Find this article interesting? Check out these related posts: Join our Data Management User Group to connect with peers on this topic and share knowledge and expertise on all things data management.
📣Master Data Management UI Demo & Feedback Sessions
In the coming weeks, we'll be running demo & feedback sessions on our new Master Data Management UI. You'll get to see an exclusive demo of our new UI and provide your feedback and insights in a small focus group setting. Available Sessions (login required): Session 1: Thursday, 13 June (3:30 PM - 4:15 PM BST) https://community.quantexa.com/events/157 Session two: Wednesday, 19 June (9:15 AM - 10:00 AM BST) https://community.quantexa.com/events/158-exclusive-master-data-management-ui-demo-feedback-session-2 Session three: Thursday, 27 June (3:00 PM - 3:45 PM BST) https://community.quantexa.com/events/159 Don't forget to subscribe to the User Research Panel page to stay up to date with other research opportunities!Entity Quality Management for Data Quality?
Data quality is one of the major challenges that organizations suffer from, consuming up to 50% of data users time, costing up to 30% loss in revenue and destroying trust in data. In today's data-dependent business environment, the urgency for impeccable data quality is driven by a confluence of market forces. Fears of reputational damage due to data mishaps, the competitive pressure from digital-first competition, and an array of stringent regulations are pushing companies to reassess their data management strategies. Quantexa's Entity Quality Management (EQM) solution enhances the efficiency and effectiveness of data remediation by tailoring campaigns to align with evolving business needs. It directs remediation activities through the efficient remediation channels, from hands-on steward workflows to automated prompts in customer portals and CRM systems. Validated in production environments, Quantexa's EQM solution has integrated more than 80 data sources, achieved a 9% rate of deduplication, and uncovered 2.5 million matches that competing solutions overlooked. Simultaneously, it has effectively identified cases of overmatching and facilitated the prioritization and support of 1,000 merge reviews on a weekly basis. How does it work? Quantexa's Entity Quality Management solution seamlessly ingests a wide array of data, irrespective of its origin, embracing both internal and external sources with a model-agnostic approach that ensures rapid integration. It employs sophisticated AI/ML models to automatically parse, cleanse, and standardize data, laying the groundwork for a consistent and reliable data foundation. Source records are then transformed into an accurate single entity view, thanks to Quantexa's scalable and highly-accurate entity resolution capability. The solution assesses each record, applying a set of rules designed to identify and rectify any anomalies, such as historical overlinking, underlining, potential duplicates, and various attribute inconsistencies, enriching the data's integrity and reducing false positives. The user experience is elevated through interactive dashboards that provide dynamic visualizations, breaking down data by various quality indicators, technical specifications, and business attributes, thus enabling a thorough understanding of data quality and the focused identification of areas for remediation. By leveraging Quantexa’s EQM solution, organizations achieve situational awareness of data quality across the enterprise, enabling a focused approach to remediation. As a result, businesses can prioritize their data quality efforts efficiently, targeting areas of most significant impact and aligning remediation tasks with current business priorities and operational demands. Integration with key enterprise services facilitates a seamless and effective data quality management process.Exploring the Challenges of Achieving a Single View in Datawarehousing
When it comes to achieving a single view of individuals or businesses in Datawarehousing, several key insights emerge: 1️⃣ Data Integration: Integration is a critical aspect. Organizations often struggle with merging data from disparate sources such as customer databases, transaction systems, and marketing platforms. Ensuring seamless data integration is essential for a unified view. 2️⃣ Data Quality: Data quality plays a vital role in establishing a reliable single view. Inaccurate, incomplete, or inconsistent data can hinder decision-making and analysis. Implementing data cleansing processes and validation mechanisms are crucial steps towards maintaining high-quality data. 3️⃣ Data Silos: Data silos, where information is isolated within different systems or departments, pose a significant challenge. Overcoming these silos requires breaking down barriers, implementing data governance practices, and establishing data sharing mechanisms. 4️⃣ Business Context: Contextual understanding is crucial for creating a comprehensive view. Data needs to be interpreted within the specific business context to derive meaningful insights. Adapting to evolving business requirements and aligning data consolidation efforts accordingly is vital. Questions I always have and continue to ask are: 🔸 How do you address the complexities of data integration when combining data from diverse sources? 🔸 What approaches have you found effective in ensuring data quality throughout the process? 🔸 Have you encountered challenges in breaking down data silos? How did you overcome them? 🔸 How do you incorporate the business context into your data consolidation efforts? 🔸 Are there any specific tools or technologies you recommend for achieving a single view in Datawarehousing? Please share your thoughts and let's learn from one another!Aug 3 Webinar: The Power of “Contextually Connected Entities” for Maximising Decision Intelligence
As defined by Gartner, Decision Intelligence improves decision-making by understanding and engineering how decisions are made, and how outcomes are evaluated, managed, and improved by feedback. Using artificial intelligence, Decision Intelligence unlocks the power of entity resolution and graph analytics to turn data into accurate decisions at scale. This means that data becomes more than the sum of its parts– not piecemeal, siloed, and afflicted with poor quality. Decision Intelligence connects all data from previously siloed and scattered points and creates as single trusted, and reusable resource. Join me and Melissa Ferrer, Partner, Data & AI, at Deloitte in a Live webinar as we delve deeper in to Decision Intelligence, and the importance of Contextually Connected Entities in having informed decisions. Event page on the community: Webinar: The Power of “Contextually Connected Entities” for Maximising Decision Intelligence The business world is more data-driven than ever, but making sense of the vast amounts of data available can be a daunting task. Many businesses struggle to bridge the gap between data and decision making, and often lack a comprehensive view of their customers. OR direct event landing page: https://info.quantexa.com/decision-intelligence-webinar-apac?hs_preview=Novfdgge-122643133495To use a Graph DB or not?
Graph databases (Graph DB) are gaining popularity as an alternative to traditional relational databases due to their ability to manage highly interconnected data. However, the decision of whether or not to use a Graph DB is dependent on several factors and is not straightforward. Some users of Graph DB technology have expressed frustration due to a lack of tangible business outcomes after investing in projects for two years or more. They are now questioning the need to continue using the technology and paying for licenses and maintenance. Some of the most complained about aspects were performance issues, complexity and flexibility. It is essential to note that Graph DB technology is not a "magic stick" and requires significant pre-work to create meaningful connections between data. Despite its advantages in managing complex data relationships, Graph DB is a data store after all, and has some shortcomings. If you have experience using Graph DB , I would love to hear about your experience and what use cases you've use/ed it for. CheersRecording for The Power of “Contextually Connected Entities” for Maximising Decision Intelligence
Hi everyone! If you've missed the webinar on The Power of “Contextually Connected Entities” for Maximising Decision Intelligence, you can now watch it on demand using the below link! https://info.quantexa.com/decision-intelligence-webinar-apac-deloitte We're keen to hear your thoughts on the topic, so please leave it below! CheersJoin the Conversation: Highlights from Solution & Industry User Groups 💬
Did you miss out on the latest discussions in our Financial Crime, Insurance, KYC and Data Management Specialist User Groups? Here's what you might have missed: Join a group to stay up to date: 💵 Financial Crime 🛡️ Insurance 🙋♀️ KYC - Know Your Customer 💻 Data ManagementCheck out the latest content from our Specialist User Groups!
The Quantexa Specialist User Groups provide opportunities to network and join industry and solution focused conversations! Check out the latest content from our Data Management, Financial Crime, Insurance, and KYC groups below. All Investigations are created equal…right? by Decision Intelligence is the Key To Stopping Modern Slavery And Human Trafficking by Advancing Correspondent Banking Insights: Identification of non-customer entities by The changing shape of fraud in the UK market - ABI Fraud Statistics by TransUnion: Synthetic Identity Fraud Growing to Record Levels by If you haven’t already why not join a user group today: 💻 Data Management Open the door to a truly connected view across all your data assets from across internal and external sources, improve data quality, build applications, and take control of master data. 💵 Financial Crime Unlock value in order to make smarter and more informed risk and intelligence-based decisions. 🔍 KYC- Know Your Customer Shift back to the core purpose of KYC in understanding the risk associated with prospects, customers and their related activity across the life cycle. 🛡️ Insurance Brings together all things to do with insurance at Quantexa and looks to enable customers, partners, colleagues and insurance thought leaders to share expertise. ❗️If you have a suggestion for another Specialist User Group you would like to see, please comment below 😊 Find more of the best content from across the Community in our monthly digest: What Happened on the Quantexa Community in August
