by Thor Olavsrud

Teradata Unveils Big Data Apps

Feb 11, 20153 mins
AnalyticsBig DataSoftware Development

Pre-built big data app templates will allow data scientists to create purpose-built apps to answer specific business questions for business users.

self service big data
Credit: Thinkstock

Seeking to make it easier than ever for business users to access insight from big data, Teradata on Wednesday rolled out a suite of new pre-built big data app templates powered by the Teradata Aster AppCenter framework.

“When you look at it, it’s the business users who really need the big data insights,” says Arlene Zaima, strategic intelligence program manager at Teradata. “They’re making the business decisions, some pretty impactful decisions, based on the insights derived from big data. Unfortunately, they don’t speak the language. The answer is big data apps. With big data apps, we can provide the data in a very easy to use interface with the tools they’re used to interacting with”

With AppCenter and the templates released today, Zaima says data scientists can purpose-build apps to answer specific business questions and deploy those apps to business users via a Web-based portal. The apps feature intuitive interfaces and visualizations that make answers “pop.”

“Self-service big data apps that are designed to answer specific business questions have the opportunity to support data-driven decision-making and drive pervasive adoption of big data solutions across any organization,” says Dan Vesset, program vice president, big data and analytics research, IDC. “Teradata has taken a significant step forward by expanding its technology solutions to include applications that make the analytics accessible and consumable for the typical business user.”

The pre-built templates are industry specific. The verticals include retail, telco and cable, healthcare, travel and hospitality, entertainment and gaming and consumer financials. For instance, retail app templates include Paths to Purchase, Attribution (multi-channel), Shopping Cart Abandonment, Checkout Flow Analysis, Website Flow Analysis, Customer Product Analysis and Market Basket and Product Recommendations.

As an example, the Path to Surgery healthcare app identifies the common path and behavioral patterns that lead to surgical procedures, like knee surgery. With the app, business analysts can predict the type of individual who might require the procedure, identify preventive measures to improve health and avoid surgery and identify the most successful pre-surgical steps to take if surgery is required.

The apps run on Teradata Aster Discovery Platform, which makes them highly scalable — regardless of data volume — and provides Web services like authentication and authorization for secure deployment.

“As your data volumes grow, your apps are not going to break,” Zaima adds.

Zaima notes that AppCenter will be available in the second quarter of 2015.

The company is also making strides in helping organizations manage the data lakes enabled by Hadoop Distributed File System (HDFS) with its metadata management technology, Loom. On Wednesday, Teradata announced Loom 2.4, which will be made available on March 31.

“It is common for data lakes to be filled with massive amounts of undefined, ungovernable and inaccessible data,” says Scott Gnau, president of Teradata Labs. “Teradata Loom offers breakthrough capability to maximize the value of the data lake with automated tools that shrink the learning curve, decrease complexity and speed the generation of exceptional insights to business users. Instead of taking months, big data analytic projects can now advance in hours.”

The newest version of Loom adds support for comprehensive data lineage, integrated metadata and Java Script Object Notation (JSON) data — the most common format for data from Internet of Things (IoT) devices, mobile devices sensors and Web browsers. The new version also adds support for partitions to better organize data in Hive, providing faster query performance.