About one year ago, Teradata Aster launched a powerful new way of integrating a database with Hadoop. With Aster SQL-H™, users of the Teradata Aster Discovery Platform got the ability to issue SQL and SQL-MapReduce^® queries directly on Hadoop data as if that data had been in Aster all along. This level of simplicity and performance was unprecedented, and it enabled BI & SQL analysts that knew nothing about Hadoop to access Hadoop data and discover new information through Teradata Aster.

This innovation was not a one-off. Teradata has put forward the most complete vision for a data and analytics architecture in the 21st century. We call that the Unified Data Architecture™. The UDA combines Teradata, Teradata Aster & Hadoop into a best-of-breed, tightly integrated ecosystem of workload-specific platforms that provide customers the most powerful and cost-effective environment for their analytical needs. With Aster SQL-H™, Teradata provided a level of software integration between Aster & Hadoop that was, and still is, unchallenged in the industry.

Teradata Unified Data Architecture™

Today, Teradata makes another leap in making its Unified Data Architecture™ vision a reality. We are announcing SQL-H™ for Teradata, bringing the best SQL engine for data warehousing and analytics to Hadoop. From now on, Enterprises that use Hadoop to store large amounts of data will be able to utilize Teradata’s analytics and data warehousing capabilities to directly query Hadoop data securely through ANSI standard SQL and BI tools by leveraging the open source Hortonworks HCatalog project. This is fundamentally the best and tightest integration between a data warehouse engine and Hadoop that exists in the market today. Let me explain why.

It is interesting to consider Teradata’s approach versus alternatives. If one wants to execute SQL on Hadoop, with the intent of building Data Warehouses out of Hadoop data, there are not many realistic options. Most databases have a very poor integration with Hadoop, and require Hadoop experts to manage the overall system – not a viable option for most Enterprises due to cost. SQL-H™ removes this requirement for Teradata/Hadoop deployments. Another “option” are the SQL-on-Hadoop tools that have started to emerge; but unfortunately, there are about a decade away from becoming sufficiently mature to handle true Data Warehousing workloads. Finally, the approach of taking a database and shoving it inside Hadoop has significant issues since it suffers from the worst of both worlds – Hadoop activity has to be limited so that it doesn’t disrupt the database, data is duplicated between HDFS and the database store, and performance of the database is less compared to a stand–alone version.

In contrast, a Teradata/Hadoop deployment with SQL-H™ offers the best of both worlds: unprecedented performance and reliability in the Teradata layer; seamless BI & SQL access to Hadoop data via SQL-H™; and it frees up Hadoop to perform data processing tasks at full efficiency.

Teradata is committed to being the strategic advisor of the Enterprise when it comes to Data Warehousing and Big Data. Through its Unified Data Architecture™ and today’s announcement on Teradata SQL-H™, it provides even more performance, flexibility and cost-effective options to Enterprises eager to use data as a competitive advantage.

Last month in New York we completed the 4^th and final event in the Big Analytics 2012 roadshow. This series of events shared ideas on practical ways to address the big data challenge in organizations and change the conversation from “technology” to “business value”. In New York alone, 500 people attended from across both business and IT and we closed out the event with two speaker panels. The data science panel was, in my opinion, one of the most engaging and interesting panels I’ve ever seen at an event like this. The topic was on whether organizations really need a data scientist (and what’s different about the skill set from other analytic professionals). Mike Gualtieri from Forrester Research did a great job leading & prodding the discussion.

Overall, these events were a great way to learn and network. The events had great speakers from cutting-edge companies, universities, and industry thought-leaders including LinkedIn, DJ Patil, Barnes & Noble, Razorfish, Gilt Groupe, eBay, Mike Gualtieri from Forrester Research, Wayne Eckerson, and Mohan Sawhney from Kellogg School of Management.

As an aside, I’ve long observed that there has been a historic disconnect between marketing groups and the IT organizations and data warehouses that they support. I noticed this first when I worked at Business Objects where very few reporting applications ever included Web clickstream data. The marketing department always used a separate tool or application like Web Side Story (now part of Adobe) to handle this. There is a bridge being built to connect these worlds – both in terms of technology which can handle web clickstream and other customer interactional data, but also new analytic techniques which make it easier for marketing/business analysts to understand their customers more intimately and better serve them a relevant experience.

We ran a survey at the events, and I wanted to share some top takeaways. The events were split into business and technical tracks with themes of “data science” and “digital marketing”. Thus, the survey data compares the responses from those who were more interested in technology than the business content, so we can compare their responses. The survey data includes responses from 507 people in San Francisco, 322 in Boston, 441 in Chicago, and 894 in New York City for a total of 2164 respondents.

You can get the full set of graphs here, but here are a couple of my own observations / conclusions in looking at the data:

1)      “Who is talking about big data analytics in your organization?” – IT and Marketing were by far the largest responses with nearly 60% of IT organizations and 43% of marketing departments talking about it. New York had slightly higher # of CIO’s and CEO’s talking about big data at 23 and 21%, respectively

2)      “Where is big data analytics in your company” – Across all cities, “customer interactions in Web/social/mobile” was 62% – the biggest area of big data analytics. With all the hype around machine/sensor data, it was surprisingly only being discussed in 20% of organizations. Since web servers and mobile devices are machines, it would have been interesting to see how the “machine generated data” responses would have been if we had taken the more specific example of customer interactions away

3)      This chart is a more detailed breakdown of the areas where big data analytics is found, broken down by city. NYC has a few more “other.” Some of the “other” answers in NYC included:

1. Claims
2. Client Data Cloud
3. Development, and Data Center Systems
4. Customer Solutions
5. Data Protection
6. Education
7. Financial Transaction
8. Healthcare data
9. Investment Research
10. Market Data
11.  Predictive Analytics (sales and servicing)
12. Research
13. Risk management /analytics
14. Security

4)      “What are the Greatest Big Analytics Application Opportunities for Businesses Today? – on average, general “data discovery or data science” was highest at 72%, with “digital marketing optimization” as second with just under 60% of respondents. In New York, “fraud detection and prevention” at 39% was slightly higher than in other cities, perhaps tied to the # of financial institutions in attendance

In summary, there are lots of applications for big data analytics, but having a discovery platform which supports iterative exploration of ALL types of data and can support both business/marketing analysts as well as savvy data scientists is important. The divide between business groups like marketing and IT are closing. Marketers are more technically savvy and the most demanding for analytic solutions which can harness the deluge of customer interaction data. They need to partner closely with IT to architect the right solutions which tackle “big analytics” and provide the right toolsets to give the self-service access to this information without always requiring developer or IT support.

We are planning to sponsor the Big Analytics roadshow again in 2013 and take it international, as well. If you attended the event and have feedback or requests for topics, please let us know. I hear that there will be a “call for papers” going out soon. You can view the speaker bios & presentations from the Big Analytics 2012 events for ideas.

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/

Who do you believe in more – Santa Claus or Data Scientists? That’s the debate we’re having in New York City on Dec 12^th at Big Analytics 2012. Due to the sold-out event this panel discussion will be simulcast live to dig a little deeper behind the hype.

Some believe that data scientists are a new breed of analytic professional that mergers mathematics, statistics, programming, visualization, and systems operations (and perhaps a little quantum mechanics and string theory for good measure) all in one. Others say that Data Scientists are simply data analysts who live in California.

Whatever you believe, the skills gap for “data scientists” and analytic professionals is real and not expected to close until 2018. Businesses see the light in terms of data-driven competitive advantage, but are they willing to fork out $300,000/yr for a person that can do data science magic? That’s what CIO Journal is reporting with the guidance that “CIOs need to make sure that they are hiring for these positions to solve legitimate business problems, and not just because everyone else is doing it too”.

Universities like Northwestern University have built programs and degrees in analytics to help close the gap. Technology vendors are bridging the gap to make new analytic techniques on big data tenable to a broader set of analysts in mainstream organizations. But is data science really new? What are businesses doing to unlock and monetize new insights? What skills do you need to be a “data scientist”? How can you close the gap? What should you be paying attention to?

Mike Gualtieri from Forrester Research will be moderating a panel to answer these questions and more with:

• Geoff Guerdat, Director of Data Architecture, Gilt Groupe
• Bill Franks, Chief Analytics Officer, Teradata
• Bernard Blais, SAS
• Jim Walker, Director of Product Marketing, Hortonworks

Join the discussion at 3:30 EST on Dec 12^th where you can ask questions and follow the discussion thread on Twitter with #BARS12, or follow along on TweetChat at: http://tweetchat.com/room/BARS12

… it certainly beats sitting up all night with milk and cookies looking out for Santa!

The conversation around “big data” has been evolving beyond a technology discussion to focus on analytics and applications to the business.  As such, we’ve worked with our partners and customers to expand the scope of the Big Data Summit events we initiated back in 2009 and have created Big Analytics 2012 – a new series of roadshow events kicking off in San Francisco on April 19, 2012 .

According to previous attendees and market surveys, the greatest big data application opportunities in businesses are:

- Digital marketing applications such as multi-channel analytics and testing to better understand and engage your customers

- Using data science and analytics to explore and develop new markets or data-driven services

Companies like LinkedIn, Edmodo, eBay,  and others have effectively applied data science and analytics to take advantage of the new economics of data. And they are ready to share details of what they have learned along the way.

Big Analytics 2012 is a half-day event, is absolutely free to attend, and will include insight from industry insiders in two different tracks: Digital Marketing Optimization, and Data Science and Analytics. Big Analytics 2012 is a great way to meet and hear from your peers such as: executives who want to learn more about leveraging advanced analytics to a competitive advantage, interactive marketing innovators who want access to “game changing” insights for digital marketing optimization, enterprise architects and business intelligence professionals looking to provide big data infrastructure and data scientists and business analysts who are responsible for developing new data-driven products or business insights.

Come to learn from the panel of experts and stay for an evening networking reception that will put you in touch with big data and analytics professionals from throughout the industry. Big Analytics 2012 will be coming soon to a city near you. Click here to learn more about the event and to register now.

Tomorrow, I will have the pleasure of presenting “Radical Loyalty – Data Science Applied to Marketing” at the GigaOm Structure:Data event with Marc Parrish, the VP of Membership and Customer Retention Marketing at Barnes & Noble. In contrast with most talks at this event, Marc and I will be focusing on the business opportunities of Big Data and specifically on marketing loyalty programs and how they relate to Big Data analytics.

The concept of a loyalty program is certainly nothing new. Brick and mortar companies have been leveraging customer loyalty in a variety of unique ways for decades. What’s different is the ability of businesses to use new types of data to take their customer loyalty insights and strategies to a completely new level. At tomorrow’s conference, we will explore ways in which modern retailers like Barnes & Noble with a strong digital marketing strategy leverage their customers’ loyalty using Big Data and how to make loyalty programs worthwhile for customers and their needs.

Barnes & Noble has proven an ability to innovate their business model by leveraging data. I look forward to sharing some insight with Marc on retail and other real world applications of Big Data.

Yesterday I presented at the Los Angeles Teradata User Group on the topic of “Data Science: Finding Patterns in Your Data More Quickly & Easily with MapReduce”. One point discussed was the common misnomer that big data is about volume, which is certainly part of the issue organizations are facing. However, the big story in big data is the complexity and additional processing required to make “unstructured” data actionable through analytics. This is where procedural frameworks like MapReduce can help. Here is a great post by Teradata’s own Bill Franks about unstructured data which helps describe the requirements unstructured data demands in the context of analytics.

As Franks notes, “the thought of using unstructured data really shouldn’t intimidate people as much as it often does.” Read more to learn why.