Organizations must adjust their strategies to fluctuating economic conditions to compete effectively. Short term wins and greater risk-taking might have paid off for companies sprinting through boom times. However, crossing the finish line in the current environment requires greater efficiency and prudent use of resources.    

The Q2 2009 issue of Teradata Magazine focuses on the improved productivity and effectiveness that data warehousing and business intelligence (BI) can uncover and enable.     

Senior director of enterprise BI at Cisco Systems, Kevin Bolden, explores ways to leverage data in lean times. Randy Lea, vice president of Global Product and Services Marketing at Teradata, explains the value of data mart consolidation in reducing costs and making more intelligent decisions.    

Innovative organizations such as Poste Italiane, SNS Bank and ARC provide prime examples of how to better serve, communicate with and retain customers by tapping into the capabilities of an enterprise data warehouse.      At street level, growing numbers of IT professionals are facing a tough job market by honing their skills and broadening their knowledge through certification.     

As companies rethink the traditional workplace—often as a means to reduce office expenses—the number of remote workers is rising. This brings new opportunities and challenges for IT and management.     

Revitalizing an existing data warehouse is just one way businesses are making the most of what they have. For those just starting a data warehouse implementation, careful planning is required.      

In Tech2Tech, Larissa Moss, president of Method Focus Inc., presents her Business Intelligence Roadmap. Learn about the new Teradata Virtual Storage option which enhances system management by enabling optimal system balance in the data warehouse. In addition, we examine how query banding can provide more detail in workload management and workflow analysis.    

In the long run, organizations need to rethink their business operations to become leaner and improve agility if they are to succeed. Please visit http://www.teradata.com/tdmo/ to access these articles and more. 

    Lots of companies are looking to reduce energy expenses and fuel costs by finding the added benefit of reducing their environmental impact. The Q1 2009 issue of Teradata Magazine explains how data solutions can enable green innovation and often improve an organization’s bottom line.

    For many organizations, identifying and analyzing potential green initiatives requires accessing clear, complete and accurate data. Sustainability leaders leverage their data to monitor business practices to ensure they are meeting targets for energy usage and fuel consumption.

     Sustainability is only one area where data can be applied for exceptional results. Teradata customers rely on their data to conduct in-depth analytics to accentuate their agility and response times. For businesses looking to implement an Active Enterprise Intelligence™ environment, data services can provide a necessary bridge to a comprehensive and successful data solution.

     One way Teradata is tailoring solutions to its customers’ specific needs is through the Teradata Accelerate program. In our Tech2Tech section, we examine how this approach bundles hardware, software and services to fit a company’s needs. This issue of the magazine also includes tips on how to perform a software upgrade from the Service Focus Team, a committee of the Teradata PARTNERS User Group, which works closely with Teradata on issues related to support services and other areas.

     Clearly, top companies consistently find new and exciting ways to leverage their data to improve their operations. Enabling new and exciting green initiatives is only one way we see the power of data.     Please visit http://www.teradata.com/tdmo/ to access these articles and more.  And make sure you check back at the end of May for the all-new Q2 issue that focuses on what organizations must do to adjust their strategies to compete effectively during fluctuating economic conditions.

Imagine if you could talk to each one of your customers one-on-one. Like they’re your neighbor or babysitter or cousin.

In the next issue of Teradata Magazine, we talk to Kari Opdal who leads CRM at Gjensidige, the largest property and casualty insurance company in Norway. In her story, Kari introduces an idea that stuck with me – the idea of using CRM to create one million segments of one.

Wow. Consider the power in that. That’s more than just a marketing tactic; it’s a shift of the entire business model… moving from product-focused selling to a customer-focused approach.

The foundation is the ability to track and understand individual customer behavior. In the next issue of Teradata Magazine, you can hear how Kari got there – and what impact it’s had on Gjensidige’s business.

Whenever a new software release comes out, it’s easy to think “Great. More work.” I even cringe whenever I see a new update in iTunes – I get terrified that things will change and I’ll have to re-learn the ropes.

That being said, I’m here to report good news.

In the next issue of Teradata Magazine we answer user questions about Teradata 13 – including how much effort is required to place the data on the right storage (Teradata 13 adds virtual storage capabilities to the Teradata Database).

The answer is none. No extra administrative effort is required. Teradata Virtual Storage fully automates data placement on the physical storage.

You ask, “How?”  

First, each allocation unit is monitored for its access frequency. Then, the access pattern is used to place the allocation unit on the part of the storage pool that corresponds with the performance for data with that pattern. Data placement is optimized within zones on a single spindle and among multi¬ple spindles that have different performance characteristics.

Because Teradata Virtual Storage operates at the allocation unit level, parts of a single table can be optimized differently: The hot partitions will be placed on faster storage, and the cool ones will be placed on slower parts of the disk pool.

More of your Teradata 13 questions will be answered in the print issue of the Magazine.

In the next issue of Teradata Magazine, Carrie Ballinger answers questions about query concurrency – likening the database to the busy Los Angeles freeways. But, like the drivers on the LA interstates, we just can’t wait. Here’s one of the questions Carrie addresses in the next issue.

 

Q. Some of my queries have long answer sets. Since I’m using a lot of throttles, I am concerned that these queries are holding onto a query slot while the long answer set is being returned. When is the query considered com¬plete, and at what point is the counter lowered so the next query can begin running?

A. The query is considered finished when the final database step has completed and the last-completed AMP worker task is released. This is before the BYNET driver returns the answer set. Even if the answer set is large, your next query can begin execution without having to wait for the client to receive the entire answer set.

 

One of the key capabilities of Teradata 13 will be virtual storage.  This is not the “virtual storage” that my kids used to use to almost put their clean laundry away. It’s much, much cooler than that.

What is virtual storage in Teradata?

Here’s how it works:

The AMP’s link to the physical disks is eliminated, and all disks connected to a group of nodes, or clique, are treated as one storage pool. Storage is handed out as needed in small allocation units to AMPs and can be returned to the pool if required.

All of the unique properties of the Teradata shared-nothing logical architecture are preserved with an assignment of each allocation unit to a single AMP, despite sharing the physical disks. Teradata Virtual Storage is imple¬mented transparently at the storage level, so no changes are required to applications using the Teradata Database.

 

 

Traditional media outlets have used demographics to target potential consumers for a long time. We’ve seen these stats for years… male, 40–55 years old, household income of $100–$150K… And for long time, that’s all we had to base decisions on.

But media is a-changing. With the emergence of new media outlets – particularly those online –we find that demographics aren’t telling the full tale. Today, campaigns are more efficient when they focus on people’s actions and behaviors.

Tim Bridges (who guest writes a column on this topic in the next Teradata Magazine) calls these behavioral profiles…. How we behave as a parent, a trader, or a cook. And it’s only when we combine the demographics with these “behaviors” that we can see the true persona of our customers.

Why is this so important? In his column, Bridges shares a startling stat from ZenithOptimedia’s Global Advertising Analysis:

“Worldwide advertising waste – money spent on messages that reached the wrong audience or none at all – reached more than $200 billion in 2007.”

That’s a lot of dough.

So, how do we get these behavioral profiles?

Digital media outlets offer us more information about customers. In turn, we gain the ability to increase the sophistication in our marketing – adding channels and finely segmenting and tuning our messaging.

But that also presents a challenge … growing and complex data is only useful if you have the ability to analyze it.  

Sounds like a Catch 22. But the payoff is worth it.

Tim Bridges of Capgemini explains more in his guest column in Teradata Magazine – hitting mailboxes soon.

In the next issue of Teradata Magazine, Thomas C. Redman offers us 10 Habits for Data Quality. Among his list of must-have habits, “The Data Doc” asks us to change the way we think about data users. Instead of thinking of your peers as just data users (or other mild expletives), think of them as your customers. How can you serve them?

It’s the idea of putting your feet in the other man’s shoes… Stepping onto the other side of the fence… and thinking about what you would need if faced with someone else’s challenges.

Shifting your perception may help you break down data quality roadblocks. You will be in a better position to understand how you can work together. And improve data quality.  

This shift cannot be done with the flip of a switch, however. And there are nine more habits impacting data quality.

Find them in the next print issue of Teradata Magazine.

Another issue of Teradata Magazine is out my cubicle door and off to the presses. For this issue, we tapped into some excellent minds – experts in data quality and in technology deployment, plus our in-house Teradata Certified Professionals.

For this issue, we talked to:

•  Tim Bridges, a vice president and the Media and Entertainment Practice leader for Capgemini in North America, about online advertising and what these new sources of data can teach us about consumer behavior.
• ”The Data Doc,” Thomas C. Redman, who gave us 10 habits for data quality. Thomas is president of Navesink Consulting Group and his fourth book, “Data Driven: Profiting from Your Most Important Business Asset,” was published by Harvard Business Press in September 2008. Thomas also has a white paper on Teradata.com called “Data Warehouses and Quality: Not Just for IT Anymore.”

Look for insights from these outstanding guest writers – and more – in the next issue of Teradata Magazine. It should hit your mailbox in early December.

If you attended PARTNERS this year in Las Vegas you can download the session presentations. Use your Registration ID to login and view over 200 sessions that covered topics tailored to business, technical, management, and executive attendees.

Of the many sessions and guru presentations, one consistent, thought-provoking theme of note was analytics. It's becoming increasingly more common - and more important – to keep an eye on predicting and improving business performances in the future. This has shifted analytics from simply an application, to a service explained Oliver Ratzesberger, Senior Director, Architecture and Operations at eBay Inc.

"The metrics you know are cheap, while the metrics you don't know are expensive but also high in potential ROI," Oliver said. Eighty-five percent of eBay’s analytical workload is new and unknown, meaning that exploration is at the core of its analytics model.

As a result, eBay has instituted an architecture that allows them to better manage a growing data warehouse, referring to it as "analytics as a service." To accomodate growth, the design can't be static or dependent on specific queries. The configuration has given eBay an advanced self-service model that allows users to leverage virtual systems for their individual or department needs. Download the presentation for more information about how the approach has helped eBay deploy self-service initiatives and more rapidly bring new ideas to market.

Oliver also presented eBay's 100PB Analytical Systems Architecture and discussed the extreme scalability of processing 100PB of data daily and active/mixed workload concepts and strategies. eBay has the distinction of running the world's largest commercial enterprise data warehouse (EDW) environment at five petabytes.

Here are quick reviews of additional analytics presentations now available online:

Advancing Beyond Analytics: Aligning People, Process and Technology to Get Closer to Customers presented by Mohan Sawheny, Kellogg School of Management

Advanced Analytics play a critical role in successful CRM initiatives. The future of analytics includes new data types, real-time insights, unstructured data and collaborative analytics from individuals across the value network. Key takeaways:

• Analytics as a driver of competitive advantage
• Barriers to analytics center around people and technology
• Developing an analytics culture is a change management process
• Analytics should be embedded "end-to-end" in the customer cycle

Predictive Analytics: Building the Right Business Solution An Evolutionary Approach presented by Becky Briggs, Airlines Reporting Corporation

The key to ARC's Profitable Analytics is using different approaches to gain insight into their industry and data to drive change in processes and behavior. ARC's BI has evolved from dashboard and scorecard analysis to the highest level of business value and complexity within predictive analysis … and it has helped translate advanced analytics into economic value.

Teradata Analytical Sandbox: Experimentation and Production Play Together presented by Danny Maddox and James Scoggins, Teradata Corporation

The presentation provides validation of how Teradata Analytical Sandbox will improve efficiencies while improving the environment, and it leverages the speed of Teradata with in-database processing. Business users can utilize data in the EDW supplemented with data in the Analytical Sandbox to:

• Build new models and analytics.
• Validate and improve current models and risk analytics.
• Identify new attribute definitions to be promoted to the EDW.
• Investigate the findings and issues in the EDW data.

These are only the tip of the iceberg. Jump over to the PARTNERS website and find more valuable presentations.