26
Nov
   

Speaking of ending things on a high note, New York City on December 6th will play host to the final event in the Big Analytics 2013 Roadshow series. Big Analytics 2013 New York is taking place at the Sheraton New York Hotel and Towers in the heart of Midtown on bustling 7th Avenue.

As we reflect on the illustrious journey of the Big Analytics 2013 Roadshow, kicking off in San Francisco, this year the Roadshow traveled through major international destinations including Atlanta, Dallas, Beijing, Tokyo, London and finally culminating at the Big Apple – it truly capsulated the appetite today for collecting, processing, understanding and analyzing data.

Big Analytics Atlanta 2013 photo

Big Analytics Roadshow 2013 stops in Atlanta

Drawing business & technical audiences across the globe, the roadshow afforded the attendees an opportunity to learn more about the convergence of technologies and methods like data science, digital marketing, data warehousing, Hadoop, and discovery platforms. Going beyond the “big data” hype, the event offered learning opportunities on how technologies and ideas combine to drive real business innovation. Our unyielding focus on results from data is truly what made the events so successful.

Continuing on with the rich lineage of delivering quality Big Data information, the New York event promises to pack tremendous amount of Big Data learning & education. The keynotes for the event include such industry luminaries as Dan Vesset, Program VP of Business Analytics at IDC, Tasso Argyros, Senior VP of Big Data at Teradata & Peter Lee, Senior VP of Tibco Software.

Photo of the Teradata Aster team in Dallas

Teradata team at the Dallas Big Analytics Roadshow

The keynotes will be followed by three tracks around Big Data Architecture, Data Science & Discovery & Data Driven Marketing. Each of these tracks will feature industry luminaries like Richard Winter of WinterCorp, John O’Brien of Radiant Advisors & John Lovett of Web Analytics Demystified. They will be joined by vendor presentations from Shaun Connolly of Hortonworks, Todd Talkington of Tableau & Brian Dirking of Alteryx.

As with every Big Analytics event, it presents an exciting opportunity to hear first hand from leading organizations like Comcast, Gilt Groupe & Meredith Corporation on how they are using Big Data Analytics & Discovery to deliver tremendous business value.

In summary, the event promises to be nothing less than the Oscars of Big Data and will bring together the who’s who of the Big Data industry. So, mark your calendars, pack your bags and get ready to attend the biggest Big Data event of the year.



18
Dec
   

It’s been about two months since Teradata launched the Aster Big Analytics Appliance and since then we have had the opportunity to showcase the appliance to various customers, prospects, partners, analysts, journalists etc. We are pleased to report that since the launch the appliance has already received the “Ventana Big Data Technology of the Year” award and has been well received by industry experts and customers alike.

Over the past two months, starting with the launch tweetchat, we have received numerous enqueries around the appliance and think now is a good time to answer the top 10 most frequently asked questions about the new Teradata Aster offering. Without further ado here are the top 10 questions and their answers:

WHAT IS THE TERADATA ASTER BIG ANALYTICS APPLIANCE?

The Aster Big Analytics Appliance is a powerful, ready to-run platform that is pre-configured and optimized specifically for big data storage and analysis. A purpose built, integrated hardware and software solution for analytics at big data scale, the appliance runs Teradata Aster patented SQL-MapReduce® and SQL-H technology on a time-tested, fully supported Teradata hardware platform. Depending on workload needs, it can be exclusively configured with Aster nodes, Hortonworks Data Platform (HDP) Hadoop nodes, or a mixture of Aster and Hadoop nodes. Additionally, integrated backup nodes are available for data protection and high availability

WHO WILL BENEFIT MOST BY DEPLOYING THE APPLIANCE?

The appliance is designed for organizations looking for a turnkey integrated hardware and software solution to store, manage and analyze structured and unstructured data (ie: multi-structured data formats). The appliance meets the needs of both departmental and enterprise-wide buyers and can scale linearly to support massive data volumes.

WHY DO I NEED THIS APPLIANCE?

This appliance can help you gain valuable insights from all of your multi-structured data. Using these insights, you can optimize business processes to reduce cost and better serve your customers. More importantly, these insights can help you innovate by identifying new markets, new products, new business models etc. For example, by using the appliance a telecommunications company can analyze multi-structured customer interaction data across multiple channels such as web, call center and retail stores to identify the path customers take to churn. This insight can be used proactively to increase customer retention and improve customer satisfaction.

WHAT’S UNIQUE ABOUT THE APPLIANCE?

The appliance is an industry first in tightly integrating SQL-MapReduce®, SQL-H and Apache Hadoop. The appliance delivers a tightly integrated hardware and software solution to store, manage and analyze big data. The appliance delivers integrated interfaces for analytics and administration, so all types of multi-structured data can be quickly and easily analyzed through SQL based interfaces. This means that you can continue to use your favorite BI tools and all existing skill sets while deploying new data management and analytics technologies like Hadoop and MapReduce. Furthermore, the appliance delivers enterprise class reliability to allow technologies like Hadoop to now be used for mission critical applications with stringent SLA requirements.

WHY DID TERADATA BRING ASTER & HADOOP TOGETHER?

With the Aster Big Analytics Appliance, we are not just putting Aster and Hadoop in the same box. The Aster Big Analytics Appliance is the industry’s first unified big analytics appliance, providing a powerful, ready to run big analytics and discovery platform that is pre-configured and optimized specifically for big data analysis. It provides intrinsic integration between the Aster Database and Apache Hadoop, and we believe that customers will benefit the most by having these two systems in the same appliance.

Teradata’s vision stems from the Unified Data Architecture. The Aster Big Analytics Appliance offers customers the flexibility to configure the appliance to meet their needs. Hadoop is best for capture, storing and refining multi-structured data in batch whereas Aster is a big analytics and discovery platform that helps derive new insights from all types of data. Hadoop is best for capture, storing and refining multi-structured data in batch. Depending on the customer’s needs, the appliance can be configured with all Aster nodes, all Hadoop nodes or a mix of the two.

WHAT SKILLS DO I NEED TO DEPLOY THE APPLIANCE?

The Aster Big Analytics appliance is an integrated hardware and software solution for big data analytics, storage, and management, which is also designed as a plug and play solution that does not require special skill sets.

DOES THE APPLIANCE MAKE DATA SCIENTISTS OR DATA ANALYSTS IRRELEVANT?

Absolutely not. By integrating the hardware and software in an easy to use solution and providing easy to use interfaces for administration and analytics, the appliance allows data scientists to spend more time analyzing data.

In fact, with this simplified solution, your data scientists and analysts are freed from the constraints of data storage and management and can now spend their time on value added insights generation that ultimately leads to a greater fulfillment of your organization’s end goals.

HOW IS THE APPLIANCE PRICED?

Teradata doesn’t disclose product pricing as part of its standard business operating procedures. However, independent research conducted by industry analyst Dr. Richard Hackathorn, president and founder, Bolder Technology Inc., confirms that on a TCO and Time-to-Value basis the appliance presents a more attractive option vs. commonly available do-it-yourself solutions. http://teradata.com/News-Releases/2012/Teradata-Big-Analytics-Appliance-Enables-New-Business-Insights-on–All-Enterprise-Data/

WHAT OTHER ASTER DEPLOYMENT OPTIONS ARE AVAILABLE?

Besides deploying via the appliance, customers can also acquire and deploy Aster as a software only solution on commodity hardware] or in a public cloud.

WHERE CAN I GET MORE INFORMATION?

You can learn more about the Big Analytics Appliance via http://asterdata.com/big-analytics-appliance/  – home to release information, news about the appliance, product info (data sheet, solution brief, demo) and Aster Express tutorials.

 

Join the conversation on Twitter for additional Q&A with our experts:

Manan Goel @manangoel | Teradata Aster @asterdata

 

For additional information please contact Teradata at http://www.teradata.com/contact-us/



28
Feb
By Stephanie in Interactive marketing on February 28, 2012
   

On a recent webinar, Rob Bronson from Forrester Research pointed out that 45% of Big Data implementations are in marketing.  One of the use cases we most hear about for customers is the need to move from single-touch attribution methods like last-click and first-click to multi-channel, multi-touch attribution.  Today we announced an extension of our Digital Marketing Solutions to deliver multi-touch attribution. 

When I speak with customers about moving to multi-touch attribution it feels like hearing about HDTV for the first time.   More clarity, more detail, and a richer experience that is more like the real-life experience of consumers.  So, multi-touch attribution is basically the HD equivalent of single-touch attribution.

What’s different?  First of all, consumers interact across many touch-points, social, mobile, search, websites as well as offline channels.  Most existing attribution solutions look at multiple touch-points within a single channel, like an ad network or web visitors.  With a Big Data Analytics approach it is easier to blend more channels into the mix and find customer connections.

This is critical today, because it better reflects the customer journey.   To be customer-centric, it is critical to be able to look at your brand through the eyes of the consumer.  A few years ago, this was impossible or at least difficult and expensive.  Now Big Data marketing analytics makes it possible to see the multi-channel journeys with incredible clarity.

As consumers dynamically adopt new technologies, keeping up with them is one of today’s marketers biggest challenges.  To do that, you can’t be stuck in legacy single-touch or annual reviews of attribution.  Big Data Analytics makes it possible to discover new patterns, test new programs and iterate to optimize in the time scales that the market demands.

An additional value is that Big Data Analytics can deliver a 3D-type enhancement to attribution.  Teradata Aster gives you the ability to use different measures for each touch point so you can use uniform, variable or exponential weightings in your model in order to test and iterate to get the right approach for your business.

Another big difference using Teradata Aster to analyze attribution is to be able to link to additional data in a Teradata Data Warehouse to include Revenue, Profit and Lifetime Value which extends attribution beyond conversion to real bottom-line performance.

Lastly, the ability to integrate into the Aprimo marketing platform makes this insight actionable.   With Aster and Aprimo being part of Teradata, it becomes possible to operationalize your Big Data Analytics more effectively.

The infographic above highlights why some marketers might feel like they have an attribution problem.  You can download a PDF of it here. On the same page, you will also find a white paper we created with Aprimo to go into more detail around what attribution looks like today, and an On-Demand webinar with Forrester and Razorfish that looks at attribution in some depth.  For those who want to read more, check out an addition to this Delicious stack.

So my question for this post is – Do you have an attribution problem?  And if so, how can having multi-touch, multi-channel attribution model make it better?