DESIGN NAME: IBM Entity Insight
PRIMARY FUNCTION: Software Application
INSPIRATION: Entity Insight was designed with non-technical users' needs in mind. Securely granting access to customer data within corporations is difficult. Granting access to a company's master data is a lengthy and highly technical process, and not everyone can have access due to security and data-integrity concerns. Entity Insight enables users faster access and quicker analysis of these data sets, and users can make the connections they need much faster.
UNIQUE PROPERTIES / PROJECT DESCRIPTION: IBM Entity Insight makes data access easy by providing an interface for non-technical users to access a curated subset of the data they need. Businesses can leverage their existing big data solutions, in addition to tailored datasets they collect from various sources, to provide quick and reliable access to data. The application allows users to combine, match, and discover available customer data, as well as visually explore and discover relationships within data.
OPERATION / FLOW / INTERACTION: In Entity Insights, business analyst users are able to conduct ad hoc matching and exploration using industry-leading probabilistic matching technology. Entity Insights allows users to leverage tools and data from different source and easily analyze information all in one space. Users can analyze and explore trusted data from large databases; create private collections or ingest a collection from a spreadsheet or CSV file for matching and exploration; combine, match, discover, and explore relationships, and also to visualize relationships at various degrees of separation using tools powered by graph technology; export insights for further exploration or leverage any existing tools and embrace open source technologies such as JanusGraph, Apache Solr, Apache Kafka, and others.
PROJECT DURATION AND LOCATION: Started January 2017, made generally available December 2017, ongoing development and enhancement
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PRODUCTION / REALIZATION TECHNOLOGY: -
SPECIFICATIONS / TECHNICAL PROPERTIES: -
TAGS: entity, entities, insight, analytics, record, records, MDM, master, data, management, analyst, self-service, exploration, graph, relationships, household, connections
RESEARCH ABSTRACT: Our objective was to investigate how to make difficult to access data available non-technical users in a self-service manner for a variety of different analytics purposes, such as risk compliance, prospect list creation, and customer segmentation analysis. Our team worked within IBM's Design Thinking Framework to observe, reflect, make in a never-ending loop. We conducted interviews, surveys, collaborative design activities, and usability testing, and using online collaboration tools such as Mural, Box and Github to collaborate with each other. Our research participants were current customers, potential customers, internal SMEs, and users recruited online.
CHALLENGE: The challenge in this was to start with working hypotheses about our user and their current pain points, validate them, and iterate again based on the feedback with real users. The working hypotheses we started with varied depending on which stakeholder we talked to so we conducted stakeholder interviews to discuss differing thoughts and opinions about our the users we were targeting and what our product was meant to do and work together to align on a common understanding. From there, we were able to recruit non-technical analysts to conduct interviews and design activities with to further build on our understanding of the problem space.
ADDED DATE: 2018-02-26 21:58:06
TEAM MEMBERS (8) : Zoë Symon, Amanda Pasquali, Rene Rodriguez, Dominick Washburn, Laura Walks, Ruben Fernandez, Meghan Corbett and Chad Amon
IMAGE CREDITS: IBM Design
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