Be sure to catch SAS and Teradata’s joint presentations during PARTNERS. You can also stop by our theater at SAS Booth 206 to see our joint solutions in action.

Teradata and SAS Update Session

Paul Segal, Analytics Consultant, Teradata
Sunday, Oct. 18
10:15 – 11 a.m.
Room: Ballroom B

Teradata and SAS have partnered together on a wide range of applications, solutions and even hardware that allow the users to take the computation to the data or execute the computations in memory. This presentation will detail the history of those jointly developed solutions and highlight the new solutions that have been developed. Multiple case studies will be presented to demonstrate the business benefits of these jointly developed solutions.

Driving Big Data for SAS® High-Performance Analytics Using QueryGrid

Momolue Kiadii, Software Engineer, Teradata
Sunday, Oct. 18
2 – 2:45 p.m.
Room: 210 AB

Companies adopting the Unified Data Architecture (UDA) host big data on Teradata platforms that are each suited to different data management and analytic needs, including the Teradata Database, Teradata Aster and Hadoop. SAS High-Performance Analytics uses parallel analytical algorithms in memory to support sophisticated data visualization and modeling tasks. Together these technologies deliver the ability to solve bigger problems than ever before.

This presentation will demonstrate how Teradata QueryGrid technology and the underlying shared high-speed interconnect bring together enterprisewide data with end-to-end parallelism. You’ll learn how to prepare analytic data sets for modeling using SAS High-Performance Analytics and SAS Visual Analytics.

Invitation-Only Lunch: Innovating With Analytics

Jill Dyché, Vice President of Best Practices, SAS
Monday, Oct. 19
12 – 1:30 p.m.

We’ve all been reading about companies that were “born digital.” You know the ones: those West Coast, formerly dot-com bastions of online commerce and social media. These companies have as many developers as they do business people. They have more data scientists than users. And when it comes to technology funding, their cups runneth over.

This keynote is for the rest of us. Come hear what going digital looks like for mainstream companies that need to run operations as they innovate. They must create a digital playbook that encompasses – and transcends! – existing development pipelines and incumbent technologies. Using examples from her latest book, The New IT: How Technology Leaders Are Enabling Business Strategy in the Digital Age (McGraw-Hill), SAS Best Practices Vice President Jill Dyché will explore the collision between leadership, information and digital. She’ll discuss the role analytics and data play in innovation, and present the do’s and don’ts of forming an innovation lab. Use this session as a playbook, and as a set of lessons learned on what it takes to become a truly innovation-driven enterprise in the real world.

Seating is limited – request an invitation.

SAS® In-Database and Data Labs: Enabling the Analytics Tools Our Users Demand

Jamila Gul, Director for Strategic Programming Group, Division of Research, Kaiser Permanente
Monday, Oct. 19
2:45 – 3:30 p.m.
Room: 203 AB

Currently, the research group makes large volumes of extracts from the Teradata system to an Oracle-based system. We then join the extracted data with other data sets and run statistical models. This process is time-consuming and not very efficient in regard to processing the complex data manipulations demanded by our users.

This presentation will show how we utilized the SAS In-Database functionality with the data lab’s environment to provide a self-service and agile environment to our users. The outcome has been a tremendous gain in the response time, as well as an order of magnitude reduction in the time it takes to prepare and run statistical models.

Vodafone Uses Analytics and Automation to Create Personalized Customer Journeys

Nilanjan Sarkar, General Manager, Marketing and Communications, Vodafone Hutchison Australia
Monday, Oct. 19
2:45 – 3:30 p.m.
Room: 207 AB

The traditional way of interacting with and thinking about the customer is over. Understanding a customer’s experience at a point in time will not work. When you look at the customer experience as a journey, you stop talking at customers and start listening and responding to them.

In this presentation, Vodafone will discuss how the company has shifted from acting on discrete customer activities to developing a customer experience journey. Learn how the Teradata UDA and SAS® Analytics underpin every part of customer engagement for Vodafone, resulting in stronger growth and a deeper understanding of how experience affects satisfaction and advocacy.

How Telefonica Changed Next Best Offer Machine Using Teradata and SAS®

Daniela Rodrigues, Project and Innovation Manager, Telefonica
Tuesday, Oct. 20
9 – 10:15 a.m.
Room: 210 CD

Telefonica is the largest telco in Latin America, with over 90 million subscribers in a four-play offer. Under the VIVO brand, we sustained this leadership in a very aggressive and competitive market. We have been working on an internal consolidation process, unifying the BI areas from two different companies into a single team and culture. Our strategic plan relies on using BI and prediction models to manage customer relationships, drive company growth and support massive marketing campaigns.

In this presentation we will share how we used Teradata and SAS to transform a 30- to 40-day customer marketing process into a daily process that drives better decisions. We’ll show how, based on client information and predictive models, we are able to list more potential offers to clients.

LVM Fulfills Requirements of Solvency II With Teradata Unity and Appliance

Rainer Geißendörfer, Enterprise Architect, Teradata
Daniel Hakenjos, Data Warehouse Architect, LVM Versicherung

Tuesday, Oct. 20
3 – 3:45 p.m.
Room: 210 CD

The Solvency II Directive is a world-leading standard that requires insurers to focus on managing all of the risks facing their organization. LVM decided to have all data on a single enterprisewide risk platform – so that the data can be reused as opposed to using siloed data or creating new data marts.

In 2014, LVM implemented a new DW architecture and platform based on Teradata 2750 DW-Appliance and Teradata Unity, an active-active highly available solution. Now LVM takes full advantage of the in-database capabilities of SAS® and Teradata. Meanwhile LVM consolidated several longstanding data marts and got the flexibility and performance it was looking for.

In this presentation LVM will discuss why it took a new approach to overcome its challenges, including implementing new architecture, technologies and processes.

Agile Development of a SAS® Credit Risk Solution Running in Teradata

Henry Kolisnik, IC, Teradata
Wednesday, Oct. 21
10 – 10:45 a.m.
Room: 206 AB

This presentation covers the value of using a modified agile approach for implementing a credit scoring solution on Teradata. Based on data warehouse implementation strategies developed by Teradata, this agile approach addressed two unique challenges:

  1. The solution required SAS In-Database Analytics running on Teradata for credit risk scoring, loan loss allowance calculations and economic capital provision calculations.
  2. The solution required rigorous data management capabilities, such as end-to-end data lineage, data quality reporting and data reconciliation. The project highlights seamless integration between SAS, Informatics and the Teradata Data Warehouse platform.

 

SAS® In-Database and Data Labs: Helping Us Change User Behavior

Charles Bach, Solutions Consultant Specialist, Kaiser Permanente
Jennie Shin, Principal for Data and Analytics, Kaiser Permanente

Wednesday, Oct. 21
11 – 11:45 a.m.
Room: 303 AB

As a general practice, our users extract data from the Teradata Environment, combine it with data from other sources and use the result as the basis for creating their analytic data sets. Next, they proceed with statistical model creation and research activities. This process may take days or weeks. With the advent of SAS In-Database functionality, we have been able to eliminate the extraction process from our workflow. Instead, users are now running the statistical functions directly on Teradata.

The time savings in data preparation and model execution are tremendous. We have implemented the Data Labs facility on our systems, allowing users to bring their external data into Teradata and experiment with it. The Data Labs facility and SAS In-Database functionality help our users think twice about extracting data from the system.

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