The best minds from Teradata, our partners, and customers blog about relevant topics and features.


The explosion of interest in Artificial Intelligence (AI) is triggering widespread curiosity about its importance as a driver of business value. Likewise, Deep Learning, a subset of AI, is bringing new possibilities to light. Can these technologies significantly reduce costs and drive revenue? How can enterprises use AI to enhance customer experiences, create more insight across the supply chain, and refine predictive analytics?

PARTNERS 2017 offers the curious visionary and the creative executive plenty of education on the pragmatic business value of AI.  Here are a few of the sessions on the topic:

Autonomous Decision-Making, ML, & AI: What It Means & Why Should You Care

We’ve entered a new era of analytics with machine learning and artificial intelligence algorithms beginning to deliver on the long-promised advancement into self-learning systems.  Their appetite for vast amounts of data and the ability to derive intelligence from diverse, noisy data allows us go far beyond the previous capabilities of what used to be called advanced analytics.  To succeed, we need to understand both capabilities and limitations – and develop new skills to harness the power of deep learning to create enterprise value. This session focuses on the future of AI, emerging capabilities today; and relevant techniques; the ‘Think Deep’ framework for automating the generation and deployment of models for machine learning & deep learning. Wednesday, October 25, 2:00: PM-3:00 PM

Fighting Financial Fraud at Danske Bank with Artificial Intelligence

Fraud in banking is an arms race with criminals using machine learning to improve their attack effectiveness. Danske Bank is fighting back with deep learning – and innovating with AI – to curb fraud in banking spanning topics such as model effectiveness, real-time integration, Tensor Flow vs Boosted Decision Trees predictive models, operational considerations in training and deploying models, and lessons learned. Monday, October 23, 11:30: AM-12:15 PM.

Artificial Intelligence: What’s Possible For Enterprises Today

The sci-fi notion of AI is still a long way off – that’s pure AI. However, Pragmatic AI technology is here today and enterprises are using AI building block technologies such as machine learning to achieve amazing business results. In this session, Forrester Research VP & Principal Analyst, Mike Gualtieri, will demystify AI and explain what enterprises use cases are possible today and how to get started. Tuesday, October 24, 9:00: AM-9:45 AM. Presenter: Mike Gualtieri, Principal Analyst, Forrester Research.

Artificial Intelligence and the Teradata Unified Data Architecture (UDA)

Artificial Intelligence has entered a renaissance. Underlying this progress is Deep Learning – driven by significant improvements in Graphic Processing Units and computational models inspired by the human brain that excel at capturing structures hidden in massive datasets. Learn how AI is impacting enterprise analytics today in applications like fraud detection, mobile personalization or predicting failures for IoT. Focus on ways to leverage and extend the Teradata Unified Data Architecture today – and a new AI reference architecture – to produce business benefits. Monday, October 23, 2:00: PM-3:00 PM.

Employing Deep Neural Nets for Recognition of Handwritten Check Payee Text

The handwritten check is a primary linchpin of the customer relationship at Wells Fargo. It represents an enormous personnel cost when the bank attempts to resolve the payee field and other transaction information in handwritten form. Currently, Automatic Teller Machines (ATM) operated by Wells Fargo can recognize monetary amounts (numerical digits) in cheques utilizing neural networks trained on a standard handwritten numeral dataset. This session details the latest in image recognition and deep learning techniques to extend recognition capability to the payee field and a new capability to deploy deep neural networks with Aster and Tensorflow, in a SQL interface. Tuesday, October 24, 11:30: AM-12:15 PM. Presenters: Gary Class, Wells Fargo, and Kyle Grove, Senior Data Scientist, Teradata.

Dig in Deep into a Data Fabric Implementation Using Teradata and SAS

Banco Itau-Unibanco S.A. is one of the largest banks in Latin America and a global Top 50 bank by market cap. It operates in the retail, wholesale, private and investment banking, private equity, asset management, insurance and credit card business. The session will outline a new data fabric platform based on Teradata and SAS integration – which brought new capabilities to the credit risk analysts, in terms of amount and complex data to be used in their models. With this platform the risk teams are able to manipulate, in a dynamic and productive way, different sources of data, higher volume (about 30 times more) and new algorithms (e.g. Neural Networks) to improve models performance. The results are amazing and will be shared in detail. Wednesday, October 25, 10:30: AM-11:15 AM. Presenters: Dalmer Sella, Data Engineer, Itau and Fabiano Yasuda, Credit Modeling Manager, Itaú-Unibanco S.A.

Please be sure to check out the Session Catalog for more, and try to register early to join the “Meet-Up” sessions!

Original Blog Post: AI and Deep Learning Session Highlights for PARTNERS 2017 - Data Points 


Did you miss the live webinar?  You can listen to the replay featuring Matt Mazzarell‌, Data Scientist, Teradata. 

Video Link : 1086

Unable to View Video here?  Use this link:  Combining Text and Graph Analytics for More Context in Your Networks featuring Matt Mazzarell - YouT... 

Video Details:

    Adding more techniques in text analytics can better inform you of the working relationships in a network. Topic analysis, sentiment extraction and predictive analytics have helped large organizations solve complex problems using large volumes of communication data from various sources. This webinar sessions explores some examples of how customers have used these techniques to add more context to their networks.


Matt Mazzarell is a Data Scientist in the Teradata Aster Solutions team with experience implementing analytic solutions for many clients in the Fortune 1000 who seek to solve business problems using large and varied data sets. He has experience collecting customer requirements and prescribing specific analytic techniques across all industry verticals. Matt is responsible for several pre-packaged solutions including Communications Compliance, Product Recommender, and Healthcare Fraud. He is dedicated to enabling the non-technical user to perform analytics at scale that drive significant value for the business.




Organization Network Analysis (ONA) In Action -  Connected Commons Webinar Series


Join John Thuma and Roger Fried, two of Teradata’s renowned data scientists in a two part workshop that will give you the knowledge and tools you need to infuse behavioral and contextual analytics. You will not only know your customers, but understand what drives them.

This workshop will also introduce you to Aster Analytics on AWS and demonstrate how you can quickly launch an instance of Aster Analytics in the cloud through AWS Marketplace.

The Aster R workshop introduces a new data science package for R that combines text, machine learning, path, patterns and graph analytics at scale.

The Aster Everywhere workshop will introduce the new Aster architecture running directly on Hadoop. Learn how business analyst can quickly explore, discover and analyze raw data in Hadoop.

Register and view the full agenda, space is limited and seats are filling up quickly; reserve your spot at this complimentary workshop. We look forward to seeing you soon!

register now for 2016 R and Aster Everywhere Workshop

jthuma‌  rf186013

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