Teradata Integrated Analytics redefines speed and efficiency.

Tech2Tech

Applied Solution 3

Treasure Trove of Insight

Teradata Integrated Analytics redefines speed and efficiency.

Organizations are embracing analytic technologies for a range of innovative capabilities, such as capturing geospatial information, rolling back time to understand changes in the marketplace and monitoring their brands using unstructured data from social media channels. Separately, each capability provides value. But integrated, the analytics and diverse data offer a treasure trove of insight.

Teradata Integrated Analytics helps provide that insight by offering a comprehensive set of highly scalable capabilities that transform Teradata systems into high-performance analytic environments. The innovative technologies leverage the powerful in-data-base processing of the Teradata Database to dramatically reduce time-consuming data movement by merging analytics and data.

Meeting the Challenge Head On

The challenge with today’s ever-changing analytic environment is that silos are often implemented to meet specific data requirements for a tool or user group. However, this type of infrastructure is costly to build, maintain and use. Plus, large amounts of data must be moved across diverse systems to execute complex tasks, which is time consuming and makes it extremely difficult to combine data and methods that drive innovation.

Big Data Analytics

The Aster Data Analytic Platform complements the Teradata integrated data warehouse with big data analytics through a SQL-MapReduce framework.

To overcome these business challenges, the next-generation analytic environment must be able to support diverse data and user groups at high speeds to enable agile analytics. It must also deliver the capabilities to process big data with new and innovative techniques. These capabilities must be tightly integrated with the data and be scalable while delivering high performance with minimal data movement for overall process efficiency.

Teradata Integrated Analytics delivers these analytic capabilities required to transform the data warehouse into a next-generation environment. This analytics portfolio uses the parallel architecture of the Teradata Database for speed and scalability. It also uses in-database technology to minimize data movement and eliminate unnecessary replication for overall process efficiency. This allows users to focus on their work instead of the mechanics of moving data. In-database processing also provides users with greater data access, which facilitates self-service analytics.

High-Performance Portfolio

Teradata Integrated Analytics supports and delivers these new capabilities and data types, emerging technologies, partner optimizations and application development tools:

Key Capabilities

The Teradata Integrated Analytics portfolio offers myriad benefits:

  • Faster. In-database processing delivers high performance and scalability, allowing analysts to work faster and smarter by optimizing their processes and eliminating unnecessary data movement.
  • Comprehensive. A range of technology is available within one environment to allow multi-dimensional analytics that eliminates the need to switch from one environment to another for richer, enhanced results. Everything is managed by the database, providing workload management for the fastest, most efficient results.
  • Scalable. Teradata data warehouse integrates data from diverse sources, providing a wealth of information to drive innovative analytic insights.
  • Flexible and open. The Teradata Open Parallel Framework allows all users and partners to extend in-database capabilities quickly to deliver custom, scalable analytics. This transforms the traditional data warehouse into an analytics services environment.

—A.Z.

  • Data exploration and visualization. Interactive, in-database exploration and visualization tools and integrations allow organizations to sift through massive amounts of data to quickly understand trends.
  • OLAP optimization. Two new products simplify online analytical processing (OLAP). Teradata Aggregate Designer automates optimization of new and existing OLAP implementations, and Teradata OLAP Connector enables any MDX OLAP tool, such as Microsoft Excel, to directly access database tables without unnecessary data movement.
  • Geospatial. Native geospatial data types represent points, lines/curves and polygons. The data types are supported by more than 60 in-database spatial functions that identify properties within a hazardous area, calculate distances between customers and stores, and run density analysis to understand risk exposure.
  • Temporal. Intelligent time-aware analytics makes it easier for organizations to create a historical picture of their business transactions and activities. In-database temporal capabilities automate data management and intelligent query processing to easily roll back time to see information on a particular date.
  • Advanced analytics. Teradata ADS Generator works with data mining technology to create the data set in preparation for modeling tasks. The Teradata plug-in for R allows users to leverage in-database processing from this emerging, open-source system.
  • Agile analytics. Data labs—logical workspaces in the data warehouse where users can explore new data and test theories—enable agile analytics. Within the labs, users can add and combine information with existing data inside the warehouse without affecting other users.
  • Big data. Users can extract facts from unstructured data and use them in the Teradata platform. Teradata partners provide a solution to integrate structured and unstructured data for analysis within the database.
  • Application development. The Teradata plug-in for Eclipse enables SQL programmers to build services that can be used as part of enterprise development. Other tools and techniques accelerate the development of in-database analytics.

Open Parallel Framework

Leading technology providers can optimize their applications and tools through integrations with the Teradata Open Parallel Framework. (See figure.)

Figure: High-Performance Integrated Analytics

Click to enlarge

The framework efficiently integrates analytics for all users and partners into an environment built for speed with no data movement—no matter what the data volume. This infrastructure enables the creation of:

  • Custom services. Developers, technology partners and Teradata can create their own in-database services that leverage parallel processing. Availability and workload management can be handled by the database administrator (DBA) to ensure proper security access and predictable performance.
  • Embedded services. Teradata provides specialized functions that maximize performance by using the inner workings of the Teradata Database. Also provided are geospatial, mathematical and encoding functions to accelerate data mining and Web applications.
  • Virtual machines. This new Teradata Database capability extends in-database analytics with additional languages and systems. Teradata virtual machines and a third-party system or language can be integrated to deliver in-database execution of programs.

Delivering High Value

From its inception, the Teradata Database was designed as a highly parallel engine to enable enterprise analytics. The Teradata Integrated Analytics suite leverages the power of the database’s parallel engine for high-speed performance while eliminating data movement and associated costs.

This enables organizations to convert their data warehouses into a service environment to meet the challenges of big, complex data, mobile business intelligence (BI), social media channels and the plethora of other demands driven by new and diverse data and analytics. The high-performance, in-database technology and capabilities of Teradata Integrated Analytics help businesses deliver consistent, high-value across their user community.


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Comments
 
ARM (Aprimo Relationship Manager) leverages the advanced analytics, spatial and other capabilities within the Integrated Analtyic portfolio to enhance relationships and marketing campaigns.

5/15/2012 4:43:50 PM
— Anonymous
 
I would like to see where does the ARM fit in this eco system ?

2/25/2012 4:52:11 AM
— Anonymous
NetApp Q1-2014