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  • admin 9:51 am on July 22, 2017 Permalink
    Tags: , , Curiosity, , into, , saves, ,   

    How Curiosity Saves Your Company … And Turns Your People Into Citizen Data Scientists 

    Latest imported feed items on Analytics Matters

  • admin 9:51 am on June 23, 2017 Permalink
    Tags: 21st, , Century, , into, Recruitment   

    Big Data Brings Recruitment into the 21st Century 

    Latest imported feed items on Analytics Matters

  • admin 9:52 am on November 16, 2016 Permalink
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    Teradata Expands Managed Cloud Offering into Europe 

    Teradata Expands Managed Cloud Offering into Europe
    Germany becomes Teradata’s first European location for data warehousing as a service; meets European customers’ demands for a secure, regional, agile environment
    San Diego, California

    15, 2016 | SAN DIEGO, California,

    Teradata United States

  • admin 9:51 am on September 17, 2016 Permalink
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    Teradata’s Borderless Analytics Turns Hybrid Clouds into a Single Analytic Ecosystem 

    Provides seamless shifting of analytic workloads across a multi-system hybrid cloud environment
    Teradata United States

  • admin 9:51 am on June 16, 2016 Permalink
    Tags: , , into, Light, , R&ampD, ,   

    As Teradata Moves into Cloud, R&D Lab Steps into Light in San Diego 

    Teradata Press Mentions

  • admin 9:47 am on March 15, 2016 Permalink
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    Introducing Apache Spark into Your Big Data Architecture 

    Teradata Web Casts

  • admin 9:49 am on February 28, 2016 Permalink
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    PG and E Taps into the Internet of Things for Utilities 

    Teradata Case Studies

  • admin 9:52 am on February 17, 2016 Permalink
    Tags: Browsers, , into,   

    How To Turn Browsers Into Buyers 

    Woman BuyingAs marketers, we need to attract the attention of individual consumers, and then ultimately, drive revenue by turning browsers into buyers. But in many ways, every step along the way is becoming increasingly difficult. In this Age of Distraction, where consumers are known to switch media platforms up to 27 times an hour, it’s all too easy for marketing to be ignored, overlooked as just part of the “noise.”

    What can you do to make your messages stand out? How can you turn more browsers into buyers? I suggest focusing on two areas: relevant, individualized content and data-driven solutions.


    For a good breakdown of ways to update your current mindset, check out Mark Schaefer’s recent post, Five reasons most content marketing is FAR behind where it needs to be. Mark uses what he learned at a conference on the future of technology and journalism at Columbia University’s Pulitzer Graduate School of Journalism to turn a critical eye on how content is currently being used to connect with customers. He concludes that the business world needs to step up its game… and quickly. If you compare the pace of change of content techniques, the business world is a sloth racing against mainstream journalism’s cheetah, he points out.

    One of your top priorities needs to be creating relevant, engaging content that helps you improve the customer experience and nurture customer relationships. As Mark writes:

    Nearly every day you can find this tired advice on the web: Companies need to be in the publishing business — that we need to “think like a media company.”

    Perhaps that was true three years ago but it’s not true any more. Sure, we might be lucky and get somebody to click on one piece of content … and maybe even read it. But how do we get them to COME BACK again?

    You need a content strategy that acknowledges customers as individuals and revolves around these three points: 1) Data to understand the customer; 2) Right content; 3) Right channel. That’s why it’s so important to have…

    Data-driven solutions

    When you’re data-driven, you gain insights by listening to the information your customers provide, and then you respond with the most relevant approach for their needs. Relevance is what makes you heard above the noise. It connects you with the individual. And it’s what works best at turning browsers into buyers.

    What pulls it all together, making this kind of approach possible? A Data Management Platform (DMP). A DMP lets you collect and analyze data about your customers from every touch point. It enables an integrated 360-degree view of all your data sources, including your own first party sources and third party sources, as well. Then, it allows you to use that information to accurately target your respective audiences across a variety of marketing channels.

    In addition, with the right DMP, you can optimize media buy and advertising creative in real time. (For more about the capabilities of our Data Management Platform, see this previous post or download our free guidebook, Data Management Plan (DMP) – The missing piece in your marketing puzzle.)

    The Age of Distraction is here, and all indications are, it’s here to stay. If you want to turn more browsers into buyers, make sure you have the tools you need for true two-way communication between your brand and the customers you’re trying to reach.

    The post How To Turn Browsers Into Buyers appeared first on Teradata Applications.

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  • admin 10:34 am on February 6, 2016 Permalink
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    Webinar: Introducing Apache Spark into Your Big Data Architecture 

    Join Eliano Marques, Data Science Global Practice Lead at Think Big, a Teradata Company, and Anand Iyer, Senior Product Manager at Cloudera to learn more about Apache Spark, how to overcome obstacles, and much more!
    Teradata Events

  • admin 9:51 am on February 6, 2016 Permalink
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    Reach Deep Into History 

    by Andy Sanderson

    While Teradata® QueryGrid™ allows you to access data and enables processing across heterogeneous systems, including technologies from Apache™ Hadoop®, Teradata Aster, Oracle or even MongoDB, some of the most compelling uses involve multiple Teradata Database systems. When organizations use several Teradata platforms for various purposes, having direct SQL access across them, along with the ability to orchestrate processing between them, opens up new possibilities.

    Gain New Insights From Historical Data

    Increasingly stringent regulations require companies to keep data online and accessible for regulatory compliance over several years or more. Although the most frequently accessed data is the latest or most current data, that doesn’t mean that the older information is not useful or relevant. Data that’s been compiled over several years gives a rich perspective of the business, such as long-term trends and cyclical patterns.

    Because there is typically much more history data than current data, and the concurrency and usage of historical information is substantially less, it makes sense to store it on a separate system that has different performance and price characteristics: for example, on a Teradata 1000 or 2000 series warehouse.

    However, keeping historical and current data on separate systems has made it a challenge to gain unique insights that are possible only by analyzing the information together. But not any longer. Now, Teradata QueryGrid can be used to seamlessly join together all the historical and current information across multiple Teradata systems, without having to change the basic data structures and queries. This makes it possible to answer questions that could not be previously addressed so decision makers can better plan for the future.

    The business can generate a basic report that is run on the past year’s data stored on the integrated data warehouse (IDW).

    SELECT sales_date, SUM(sales_quantity) AS total_sales

    FROM samples.sales_fact

    GROUP BY 1

    ORDER BY 1;

    The query results returned 334 rows in 1.5 seconds. Now, if the business wants to run a full report on all of its data, including the historical data, Teradata QueryGrid can query information from all available years across the IDW and the historical data located on another Teradata system. The data on the historical database has the exact same column structure, but it is in a table called:sales_fact_history.

    By using a simple UNION to join the data across the systems, the Teradata QueryGrid foreign server object we have created in this example is called td1000:

    SELECT sales_date, SUM(sales_quantity) AS total_sales

    FROM (

    SELECT * FROM samples.sales_fact


    SELECT * FROM samples.sales_fact_history@td1000) all_sales

    GROUP BY 1

    ORDER BY 1;

    The query plan, which executes using Teradata QueryGrid, followed these steps:

    • The query was initiated from the IDW.
    • The local query on the IDW ran to select qualifying rows.
    • A remote query on the td1000 ran to select qualifying rows.
    • All rows were returned from the td1000 and placed in a spool on the IDW.
    • The IDW merged both data sets and applied aggregation to all rows.
    • The IDW applied grouping and ordering.

    This Teradata QueryGrid query resulted in 1,336 rows, and 14 million rows were transferred back to the IDW. The query took about 30 seconds to complete.

    Optimize With Push-Down Processing

    Just as you can optimize a query on a single system to perform better, you can also optimize Teradata QueryGrid queries. You need to take into consideration the performance of the individual query pieces that will happen on each system as well as the performance of the network between them.

    One of the most powerful features of Teradata QueryGrid is its ability to orchestrate processing across multiple systems and “push down” the processing when desired. This revised sales report query leverages that capability:

    SELECT sales_date, SUM(sales_quantity) AS total_sales

    FROM samples.sales_fact

    GROUP BY 1


    SELECT *


    SELECT sales_date, SUM(sales_quantity) AS total_sales

    FROM samples.sales_fact_history

    GROUP BY 1)@td1000 old_sales

    ORDER BY 1;

    To utilize Teradata QueryGrid for push-down processing, you use the keywords “FOREIGN TABLE.” This lets you initiate a subquery on the secondary system, which is everything shown in the parentheses in the preceding query.

    In this case, the 1000 series system aggregates the results for its data and sends just the results instead of all the raw data rows. This allows you to minimize the data transferred across the network as well as use the processing power of that system.

    The query plan for this push-down query using Teradata QueryGrid followed these steps:

    • The query was initiated from the IDW.
    • A local query on the IDW ran to select qualifying rows: sales_quantity aggregated.
    • A remote query on the td1000 ran to select qualifying rows: sales_quantity aggregated.
    • Qualifying rows were returned from the td1000 and placed in spool on the IDW.
    • The IDW merged both data sets.
    • The IDW applied ordering.

    The push-down version of this Teradata QueryGrid query resulted in 1,336 rows, with just 1,002 rows transferred. The total elapsed time was about four seconds. As the results demonstrate, there is a dramatic increase in performance when using the push-down capabilities of Teradata QueryGrid. But, as with any optimization, results will depend on your particular environment, such as your systems, data and network. You may also want to use push-down processing to leverage idle resources in order to free up capacity on the IDW, even if the overall performance is slower.

    Uncover More Value

    Using the push-down capabilities of Teradata QueryGrid lets you orchestrate queries to fit your business needs and data architecture. The solution enables seamless, high-performance, multi-system analytics while supporting many different platforms.

    Leveraging a company’s deep historical data to uncover new answers to business problems is just one of the ways you can use Teradata QueryGrid across multiple database systems. As more businesses continue to adopt the solution, they will find more ways it can help them uncover insights and get even more value from all their data.

    Andy Sanderson is the product marketing manager for many of the Teradata® Unified Data Architecture™ products, including Teradata QueryGrid™.

    This article originally appeared in the Q4 2015 issue of Teradata Magazine. For more on Teradata QueryGrid and how to economically scale your database environment, visit TeradataMagazine.com.

    The post Reach Deep Into History appeared first on Magazine Blog.

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