Teradata Aster Discovery Platform
Next-Generation Analytics on All Data
The Teradata® Aster® Discovery Platform is the industry's first next-generation, integrated discovery platform that provides powerful, high-impact insights from big data through an integrated solution optimized for multiple analytics on all data with speed and minimal effort. Using the Aster Discovery Platform, organizations attain unmatched competitive advantage and drive pervasive adoption of big data analytics by every user based on their skills and preferences.
Figure: Teradata Aster Discovery Platform
Next Generation Analytics for powerful insights with ease
Teradata Aster features Teradata Aster SQL-GR™ analytic engine which is a native graph processing engine for Graph Analysis across big data sets. Using this next generation analytic engine, organizations can easily solve complex business problems such as social network/influencer analysis, fraud detection, supply chain management, network analysis and threat detection, and money laundering.
In addition to the Aster SQL-GR, Aster Discovery Platform also provides SQL and SQL-MapReduce® analytic engines that enable a variety of analytics best suited to these engines, such as SQL analysis, Path/Pattern Analysis, Statistical Analysis and Text Analysis.
Multi-Type Store to Quickly Ingest ALL Data
New storage architecture that leads to novel insights with the least amount of IT effort. Teradata Aster File Store™ enables quick and easy ingest of multi-structured data, such as web logs, sensor data, machine log data etc. for analysis without any loss of fidelity or upfront schema definition effort. Aster Discovery Platform also provides row and column store for storing relational data.
Teradata Aster SNAP Framework™ for Discovery
Teradata’s revolutionary Teradata Aster SNAP Framework™ enables users to snap together multiple analytic engines and file stores with ease providing them with unmatched power and speed to delve deeply into data. The SNAP Framework includes the Integrated Optimizer and Executor, Unified SQL Interface, and Common Storage System and Services. SNAP Framework is designed to be standards-based, extensible & seamlessly integrates with existing IT infrastructures.
Figure: Teradata Aster SNAP Framework™ for Discovery
Discovery Portfolio and Interactive Visualizations drive pervasive adoption
Teradata Aster Discovery Portfolio provides a suite of ready-to-use functions applied from a familiar SQL interface for fast and easy discovery of business insights from big data. Discovery Portfolio provides four modules of functions: Data Acquisition Module, Data Preparation Module, Analytics Module, and Visualization Module.
Teradata Aster Lens is an interactive web application for business users and analysts to explore the results of analysis through interactive visualizations in a web browser. Aster Discovery Platform integrates with several leading BI and reporting tools such as Tableau, MicroStrategy, Tibco Spotfire, IBM Cognos and SAP BusinessObjects.
- Gain An Unfair Competitive Advantage — Discover powerful, high impact insights from big data through an integrated solution optimized for multiple analytics on all data. Uncover new opportunities and solutions that you didn’t know existed or were unclear by applying next generation analytics on all data with ease.
- Achieve fastest time to value by reducing complexity — Achieve business impact quickly by reducing the complexity of big data analytics. Apply unmatched power and speed to delve deeply into data with minimal effort. Empower existing resources to generate value from big data based on their current skills and preferences.
- Drive Pervasive Adoption of Big Data Analytics — By making it easy to do big data analytics and discovery, brings the science of data to the art of business so everyone can be a data scientist. From a business user to a data analyst or a data scientist, everyone can participate in the discovery of insights and apply their knowledge and expertise. This produces unmatched competitive advantage for the organization.
Use Case Example: Proactively detect and prevent customer churn - Telecommunications
Retaining existing customers and preventing churn is a key goal for Telecommunications companies. Not only do existing customers present revenue growth opportunities with increasing loyalty, costs of acquiring new customers is much more than cost of retaining existing customers. In addition, when an influencer in a social network leaves, people connected to that person are 6 times more likely to also cancel their service.
Aster Discovery Platform leads to higher customer retention by improving churn prediction and finding incremental customers at risk of churn. The telecommunications company can seamlessly combine pre-built Graph + Path + Text + Statistical Predictive Analysis available in the Aster Discovery Platform. By analyzing ALL data from all channels of interaction, the company gains a 360° view of its customers and identifies key patterns of behavior that lead to churn. Powered by these insights, the company can proactively reach out to save profitable at-risk customers.
Graph Analysis on Call Detail Records (CDR)provides insights such as who is connected to whom and who is an influential subscriber. CDR data includes information such as who calls whom and how frequently. If an influential subscriber cancels their service, not only does the company lose revenue from him or her, but other subscribers who are connected/influenced by this person are also likely to cancel their service and leave.
In addition, Text Analysis of Call Center data indicates what issues customers are having and how satisfied or dissatisfied they are. Similarly, Text Analysis of Social media data such as Facebook posts identifies the sentiment of the customer – satisfied or dissatisfied.
To understand the path of customer interactions across all channels of engagement (website, call center, store etc.) before they cancel service, Path Analysis is performed to identify the top paths and series of events leading to cancellation.
All of these insights from Text Analysis and Path Analysis are fed to a Predictive Statistical Model to identify which customers are the most likely to churn.And combined with the influencer analysis from Graph Analysis, the Telecommunications Company can proactively identify key influencers predicted to churn and more effectively retain them through targeted promotions and offers.
Gain Your Unfair Advantage with a Data Discovery Platform
with Teradata Aster
by Scott Gnau
Teradata Aster Discovery Platform Liberates Data Scientists Around the World
IDC Research Report
on Discovering the Value of a Data Discovery Platform
IDC Assessment Tool
to assess an organization’s discovery competency
Prevent Customer Churn
Option for You
Whether you are a Fortune 1000 enterprise struggling to make sense of new multi-structured data or a web company just getting your analytics infrastructure off the ground, Teradata Aster Discovery Platform lets you choose the type of deployment that best meets your needs.
- Appliance: Terada Aster Big Analytics Appliance. The industry’s first unified big analytics appliance provides a powerful, ready-to-run big analytics and discovery platform that is pre-configured and optimized specifically for big data analysis.
- Packaged software-only: Teradata Aster Database
- Cloud-based: Teradata Aster Database Cloud Edition