Teradata 2017 EPIC awards open for best business bases

Teradata (NYSE: TDC), the leading analytics solutions company, yesterday announced that entries for the 10th annual EPIC Awards are being accepted now through June 16, 2017. Award winners and finalists will be honored at an exclusive ceremony held during the Teradata PARTNERS Conference, October 22-26 in Anaheim, California.

In keeping with the conference theme, “The Edge of Next,” the Teradata EPIC awards program recognizes customers and alliance partners who achieve outstanding business results through analytics. Government agencies are also invited to participate and will be evaluated based on their ability to effectively address constituent needs. “The EPIC Awards Program recognizes organizations that are innovative in the use of data and analytics to drive game-changing business results,” said Chris Twogood, Vice President of Product and Services Marketing, Teradata.

“The Teradata community has many champions in thought leadership who know how to turn data into profitable business growth. We are looking for customer and alliance partner use cases at every level, in every area of business, and across every industry. Teradata users demand, and deliver, world-class performance.” Eligible customers are those businesses or government agencies whose submitted use case is derived from the use of any Teradata product or solution. The customer EPIC Award categories are listed below, shown with last year’s winners:

Customer Awards Category: Analytical Excellence

Solutions that improve business decision making by increasing the accuracy or speed of business insights, and by delivering measurable improvements in revenue, organizational performance and/or productivity. 2016 Winner: Anthem Inc. Project: Client Information Insights (CII) 2.0 Client Information Insights (CII) is a robust reporting and analytics solution for employers, brokers and consultants.

Category: Big Data Excellence

Winners in this category are doing groundbreaking work to deliver business outcomes using big data, and/or data lakes with BI technologies and techniques. 2016 Winner: China Merchants Bank Project: Big Data Planning Project - This big data planning project focused on technical aspects, investigated business requirements and summarized big data use case categories.

Category: Customer Journey Excellence

Solutions in this class deliver customer insights from any channel and help drive customer engagement, response, or loyalty; and implementations that optimize data-driven marketing programs. 2016 Winner: Southwest Airlines Project: Customer Centricity Transformation (CCT) - Customer Data Warehouse (CDW) - This new Technology is allowing Southwest Airlines to drive customer insights, improve customer acquisition and retention, dramatically expand customer segmentation and fully leverage its investment in its new reservation system.

Category: Collaboration and Innovation Excellence

This category honors a team of colleagues or a top Technologist or Business Leader (CIO, CMO, vice president or director) who generated a positive impact on their organization, leading integration of business and IT and the application of Teradata technology to improve his or her company’s business performance.

2016 Winner: Ken Drake, Senior Director of Business Intelligence, Blizzard Entertainment With a commitment to building strong teams, leveraging global resources and always putting the customer at the center, Ken successfully implemented the Teradata Unified Data Architecture from scratch in only six months.

Category: Integrated View of the Business

Solutions in this class deliver analytic insights by unifying the data ecosystem into a cohesive analytic environment on premises or in the public or private cloud, by harnessing data sources, data types and/or data structures across an organization. 2016 Winner: Sanofi Project: Maestro - This is the first ambitious project where the customer built an agile clinical data warehouse to address the clinical trial challenges and high variability of the increasing data volume.

Category: On the Edge with Internet of Things (IoT)

By capturing and analyzing all types of sensor data from telematics and/or interconnected devices such as vehicles, meters, machines, weather devices, buildings, manufacturing lines, and shopping carts, this emerging breakthrough business application can monetize the industrial Internet of Things by changing business models, improving processes, exploiting new technologies, improving personal health, or enhancing the customer experience in new ways. 2016 Winner: Siemens AG Project: Internet of Trains @ Siemens Mobility Services - Considered to be the leading IoT platform using the Teradata Unified Data Architecture(tm), this platform represents a new, market-leading offering of data-driven insights, opening up a new customer segment that was previously not addressable.

Category: Operational Excellence

Implementations in this class use data and analytics to deliver measurable improvements in the organization’s operations, such as forecasting or anticipating customer demand; improving inventory management, supply chain visibility or increasing sustainable business practices and resource optimization.

2016 Winner: United States Air Force

Project: Data-Driven Vehicle Management at United States Air Force - This program represents the nation’s 4th largest government vehicle fleet of over 78K assets valued at more than $7B. Integration and Consulting Partner (ICP) and Independent Software Vendor (ISV) Awards

Category: ICP and ISV Big Data Intelligence

Partners in this group will have leveraged one or more of Teradata’s platform technologies including Teradata, Teradata Aster, Hadoop, or any Teradata Cloud offering-to leverage new emerging data sources such as Web logs, sensor data, digital marketing optimization platforms, Web path analysis, or other advanced analytics for discovery and insight.

2016 Winner (ICP): IBM Global Business Services

Project: Always-On CRM Analytics - This project provides one of the top four largest financial institutions in Australia with new insights into customer behavior and experience across the bank’s international divisions by combining banking data with external data through partnerships with other industries such as telecommunications, retail, insurance, industrials and financial organizations. 2016 Winner (ISV): SAS Project: Railway Advanced Analytics Platform - This customer from the SAS-Teradata partnership, a major transportation provider, is supported by an integrated portfolio of products in Teradata’s Unified Data Architecture.

Category: ICP Business Insight

This award recognizes a partner who has developed and implemented a point solutionsuch as pre-built applications or an industry offer-that uses any analytic data platform, including Teradata, Teradata Aster, Hadoop and/or one of our analytic applications to deliver analytic insights to customers.

2016 Winner (ICP): Capgemini and Coca-Cola Refreshments

Project: Predictive Ordering - This partner has been and is currently providing a host of services in multiple areas across the value chain, offering a tailored approach to deliver services and innovations enabled by a host of capability centers.

Category: ICP and ISV Enterprise Intelligence

This award recognizes a partner who has worked with a customer to build a companywide solution leveraging a Teradata enterprise data warehouse to drive value. 2016 Winner (ICP): Accenture Project: Insights Data Lab - Over the past three years, this partner has assisted a mutual customer in moving from an IM Strategy to the selection of a new platform and the delivery execution for a new data foundation. Additionally in 2015, the first phase of a new strategy went into production with the development of an “Insights Data Lab” for advanced analytics. 2016 Winner (ISV): Fuzzy Logix and Tesco Project: Tesco Sales Forecasting Analytics - This partner and Teradata collaborated with a large retailer in Europe to implement a sales forecasting solution to accelerate forecasts, which can now be run multiple times per day and take into account multiple variables down to the store level.