Achieve a True 360° View with Quantexa Unify for Microsoft Fabric, now GA
Today, we announced the General Availability (GA) of Quantexa Unify, an AI-powered integration within the Microsoft Fabric platform that connects fragmented data at scale with speed and precision. Read our step-by-step guide on how we’re helping users create AI-ready, entity-resolved data in minutes that can deliver true 360 degree views directly into end-user applications for smarter decision-making. An enterprise 360-degree view gives organizations comprehensive visibility of their operations. It involves creating unified views of an organization's data across all departments, systems, and processes, helping integrate, analyze, and act on data holistically for better decision-making, risk management, and customer insights. It underpins industry use cases such as Customer 360 in marketing intelligence, Citizen 360 in government or Patient 360 in healthcare. With OneLake in Microsoft Fabric, organizations have a strong foundation for unifying and delivering data. OneLake collates data across silos and delivers it with ease directly into your data pipelines and business operations, overcoming challenges organizations have faced with traditional Master Data Management approaches. This includes issues like servicing distinct business needs and data acquisition strategies with disparate systems, while maintaining data consistency. However, more data can mean more duplicates, incompletions and inconsistencies which can disrupt pipelines, and prevent accurate data reaching your business when you need it. For this, Quantexa Unify, a native Microsoft Fabric Workload, now GA, adds a simple-to-use entity resolution capability. It is grounded on proven experience in the world’s largest and most demanding organizations as part of the Quantexa Decision Intelligence Platform, fundamental to applications like customer intelligence, risk identification, and event monitoring where accuracy and context matters. Let’s explore how Quantexa Unify for Microsoft Fabric can deliver de-duplicated data, through dashboards, notebooks and data pipelines and platforms, drawn from across your Fabric data estate. Providing accurate, contextual enterprise 360-degree views of individuals, organizations, locations, and other real-world entities in your Fabric tenant, ensuring PII and your data privacy compliance. Run the native workload Add the Unify workload to your Fabric tenant. From the Microsoft Fabric home page, click the Workloads button in the left navigation page. From the Add more Workloads section, click the Quantexa Unify workload to add it to your tenant. Once added, the workload appears on the My Workloads section on the same page. You are good to go! Before you create your project, ensure the Data Sources you want to use with the workload are in a suitable format to upload as lakehouse objects to Fabric. Now select the data sources. Unify will analyze the metadata, and identify the content of the data fields, then automatically map those fields to pre-defined entity resolution models. Now in a few clicks we can organize our Enterprise 360 view through optimizing data mapping and selecting our entity resolution preferences for matching that meets your needs and schemas. We’ll start by mapping data across the data sources in OneLake. Once your Data Sources are mapped, you can now resolve and create matched Entities by running an Iteration where the power of entity resolution is highlighted. In the video, we selected the default option. A sales team or an investigation team may prefer more open-ended “fuzzy” record matching view while a finance team or a marketing team adhering to GDPR may take a “strict” view. The process takes only a few minutes, with most time spent on the computational overheads of setting up the jobs. Whether handling 1 row, a thousand rows or 100 million, execution time grows only marginally, delivering near-constant performance at scale. The Quantexa Platform has been proven at 60 billion+ record volumes. It scales to the size of your OneLake data estate. You - the user - control the capacity (amount of compute), and hence you can control the performance. Power your Microsoft Fabric data pipeline Now take your accurate, deduplicated data into your end-user applications, for example: Power BI for dashboards and analysis Fabric Data Warehouse for data warehouse teams and administering data products Fabric Notebooks for data science and reporting, including Python and R Microsoft Copilot-enabled Fabric data workflows Without entity-resolved data, issues arising from unmatched, disconnected data could lead to: duplicated entries skewing statistics incorrect classifications and categorizations false positives arising from seemingly independent records that were not. Instead, when building your next data product, or using Microsoft’s predict function in a Fabric notebook, or populating your Power BI dashboard, ensure your data is AI-ready with entity resolution and Quantexa Unify. Get Started Today! Find the workload on Microsoft Fabric!
Entity Resolution Configuration & Parsing Health Checks
Entity Resolution (ER) and good Entity quality underpin all Quantexa deployments. The accuracy of Entity configuration and parsing are two areas that impact Entity quality. These articles outline Entity Resolution (ER) health checks and Parsing health checks to be carried out by the development team on deployments. This allows the team to identify, prioritize, and fix any potential underlying issues that could be reducing Entity quality. These checks must be completed as part of the initial deployment, but also periodically over the lifetime of the deployment. New product functionality, and data changing, may mean configuration needs to be changed, or enhanced over time. Topics covered: Entity Resolution Health Checks Pre-requisites Resolver JSON configuration health check steps Perform a comparison to the latest core Resolver JSON configuration Review configured Element exclusion criteria Review configured exclusions for Compounds in the relevant template Compound model health check steps Are all required Compounds being generated in ETL for the relevant Document types? Are Compounds being generated to populate elements required for exclusions in other Compounds? Do the traversals all look sensible? Do you have good coverage of unit tests? Parsing Health Checks Pre-requisites Parsing health check steps Is your deployment using the latest versions of Parsers? Has your deployment applied custom Parsing functions or wrappers? How does your Parsing compare to best practice Parsing? How well are the Parsers performing per source and country? How well-populated are the Parsed fields?
FAQ - List of Technical Business Analyst (BA) Academy Frequently Asked Questions
Below is a list of FAQ's for the Quantexa Technical Business Analyst (BA) Academy. Search configuration could not be loaded Setting up the training-tutorial project for the Scenario-based Tasks Not able to access search option on UI application. check-all.sh script showing all started UI Entity search not working BA Academy Task Part 2 CSV files missing Have an idea for an FAQ? Please let us know by emailing training@quantexa.com with the idea!
