Daily Archives: August 8, 2017

Ready for an Instant Education in Data Science? Get It at Teradata PARTNERS

August 8, 2017

Logo-ThemeLockup_Date_Horizontal_CMYK (1)More than ever, “WOW!” business outcomes are driven by data scientists, and there are many types of data scientist. Everyone can benefit from understanding the ways data scientists explore, analyze and execute strategic business decisions and plans. The 2017 Teradata PARTNERS conference offers many sessions focused on Data Science – so get an instant education on Data Science. Take a look at the options:

State of the Art Data Science for the Data Driven Enterprise – Look at Data Science in practice at Verizon Wireless! Learn how to build a data driven enterprise from experts at Verizon Wireless, which became the leading wireless carrier in part by leveraging data and analytics. You’ll see how they created a culture and processes that continue to drive results and decision-making. (Tuesday, October 24, 3:00: PM-3:45 PM, Presenter: Ksenija Draskovic, Associate Fellow in Data Science, Verizon Wireless.)

Have you seen my Data Scientist? The Building of eBay’s GCX Analytics Team – Is your team planning  to create a data science team and practice? Learn how eBay Global Customer Experience (GCX) has done it. Ebay has a successful data science organization and developed new analytic skills to build a dynamic, flexible, agile team, partnering with business users to define and deliver high value projects and actionable insights. (Tuesday, October 24, 11:30: AM-12:15 PM, Presenters: Jack McCush, Sr. Analytic Consultant, Advanced Analytics & Data Science, Teradata and Co-Presenter Phil Broadbent, Sr. Manager, GCX Analytics, eBay.)

Next Generation Data Science – For data science experts who are interested in their peers’ viewpoints on what’s next, this session has it all. You’ll learn about next-generation algorithms, enterprise grade analytics, and mixed data types. Also examine the challenges ahead as we look at next-generation platforms to integrate computing paradigms like SQL, Machine Learning and Deep Learning by best-in-class engines – and advances in parallel processing, GPUs, and in-memory computation.  (Monday, October 23, 3:30: PM-4:30 PM – Presenters: Awny Al-Omari, Teradata Aster Engineering Fellow, Teradata; Choudur Lakshminarayan, Engineering Fellow, Teradata.)

Data Science and the Privacy Paradox – This session is a new type called a “Meet Up” which is an open discussion, where you can get more time and greater access to a subject matter expert in Data Science with a special focus and interactive discussion. This session is limited to the first 15 people to pre-register for the session. (Tuesday, October 24, 4:00: PM-4:45 PM – Presenter – Liza Duffy, Data Scientist, Teradata)

Data Science Enabled Digital Experience & Operational Excellence – This session is also a “Meet Up” which is an open discussion with an expert in Data Science. Session is limited to the first 15 people to pre-register for the session. (Tuesday, Oct 24, 4-4:45 PM – Presenters: Kristi O’Grady, Principal Data Scientist, Teradata; David Stone, Product Owner – Analytics Ecosystem , Teradata Labs.)

Women in Data Science – This session is a panel discussion among Teradata Data Scientists, who will discuss their career experiences, the joys and challenges of being a female Data Scientist in the field, and ideas for mentoring and encouraging girls into Data Science careers. (Wednesday, October 25, 9:00: AM-10:00 AM – Panelists – Michelle Tanco, Data Scientist, Teradata; Amy Heinrich, Data Scientist, Teradata; Kate Phillips, Teradata; Yasmeen Ahmad, Director of Think Big Analytics.)

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

Getting value from attribution analytics, according to Gartner

August 8, 2017


I’ve learned something funny about analytics over the past few years out in the field. After nearly every discussion, the customer or prospect says, “This is great, and we definitely need it — but what do we do with the results?”

The value of analytics is almost taken for granted at this point. Companies urgently need to become data-driven just to keep up with the market. So, naturally, managers and executives want to explore opportunities to leverage analytics to improve their business. But it’s that last bit — improving the business — that we often fail to think through from the beginning.

In his blog post “Clarify Marketing Impacts with Attributions and Marketing Mix Modeling,” Gartner contributor Chris Pemberton outlines five steps for successful marketing modeling. The first and fifth steps Pemberton describes — “define the goal” and “use the results,” respectively — are the ones through which companies often want to fast-forward. But in my experience, these are indeed cornerstones to successful engagements.

Let’s consider these two steps in the context of a typical attribution project. Since we released our Attribution Guided Analytics Interface a few months ago, I’ve recently been involved in several such projects.

  • Define the goal. “Begin with the end in mind,” Pemberton writes. Do you plan to use attribution so you can drop a few visuals into an executive deck to convince your management team that you are doing it right? Or are you planning to realign marketing investments quarterly or even weekly based on the results of one or more attribution models? Or do you plan to incorporate results from attribution models into management performance incentives?
  • Use the results. The ability to use these models “separates success from failure,” according to Pemberton. If you’ve ever tried to justify your investment in analytics to executives, or if you’ve ever presented to a room full of analytics professionals, you’re undoubtedly familiar with the question, “So what?” Pemberton suggests assigning someone upfront to capture findings and log the changes you make as a result of your analyses.
The Attribution Guided Analytics Interface makes it easy for analysts to explore a variety of attribution models across products, channels and programs, and time windows. The results of these analyses can be used to reallocate marketing spend to successful channels and programs.

The Attribution Guided Analytics Interface makes it easy for analysts to explore a variety of attribution models across products, channels and programs, and time windows. The results of these analyses can be used to reallocate marketing spend to successful channels and programs.

The steps Pemberton outlines provide the type of roadmap than can transform your next marketing modeling project from a science experiment into a business initiative that impacts the bottom (or top) line. Teradata’s analytics and consulting professionals are happy to assist.

ryan-garrett-headshotRyan Garrett is senior business development manager for Think Big Analytics, a Teradata company. His goal is to help organizations derive value from data by making advanced analytics more accessible, repeatable and consumable. He has a decade of experience in big data at companies large and small, an MBA from Boston University and a bachelor’s degree in journalism from the University of Kentucky.