Data and AI: Accelerators of Banking CX

Sas

How important are data and analytics to a banker’s bottom-line objectives – growing deposits, loans and the customer base? In the latest Digital Banking Report, AI for Improved Customer Experience, almost 90 percent of respondents indicated that advanced analytics is extremely or very important to capabilities like cross-channel contextual communications, proactive advice and audience targeting.
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Spotlight

This talk outlines my journey from complete novice to machine learning practitioner. It started in November 2015 when I left my job as a project manager, and by April 2016 I was hired as a Data Scientist by a startup developing bleeding edge deep learning algorithms for medical imagery processing...

OTHER ON-DEMAND WEBINARS

Modernizing Metadata

tdwi.org

Metadata is more relevant than ever. It continues to be a powerful enabler for high-value data-driven business activities across operations, analytics, and compliance. However, to maintain this relevance, metadata management must deal with the increasing complexity of today’s business use cases and hybrid data environments. Metadata management is notoriously manual which makes it slow in development and error-prone in maintenance. Metadata management needs better tool automation. Metadata management is typically siloed due to users managing metadata per tool or platform. Metadata management needs a unified solution that is suited to sharing, reuse, governance, and comprehensive views of distributed data.
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Data Storytelling With Multiexperiences

Gartner

Discussion Topics: - What is a data story - When and how should data storytelling be used - Which new skills and techniques do you need to create compelling data stories - Which experiences can help tell your story beyond dashboards on a 2D screen
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Key Elements of a Successful Data Governance Program

At its core, Data Governance (DG) is all about managing data with guidance. This immediately provokes the question: Would you tolerate any of your assets to be managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Delegates will understand why Data Governance can be tricky for organizations due to data’s confounding characteristics.
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What is Anomaly Detection and its Role in Preventative Analytics

DataRPM

Equipment downtime is a multi-billion-dollar problem which will only continue to grow with exploding sensor data. According to IDC, by 2018 a third of industrial companies will be disrupted by “Industrial IoT enabled competitors.” So how can companies monetize their IoT investments for higher operational efficiencies and productivity? Anomaly Detection and Prediction is the silver bullet that companies need to maximize their machine uptime and performance. Watch the on-demand webinar featuring the Dean of Big Data, Bill Schmarzo, Chief Technology Officer, Big Data at Dell EMC and Seth Page, General Manager and Head of Partnerships at Progress DataRPM, to learn how zero factory downtime can be a reality.
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Spotlight

This talk outlines my journey from complete novice to machine learning practitioner. It started in November 2015 when I left my job as a project manager, and by April 2016 I was hired as a Data Scientist by a startup developing bleeding edge deep learning algorithms for medical imagery processing...

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