1010data Offers Data Warehouse-as-a-Service for Analytics Queries

by   |   September 24, 2012 9:06 am   |   0 Comments

Dollar General shopping basket

Dollar General uses 1010data to track the contents of shopping baskets to analyze correlations among consumer choices.

Among the strengths of the spreadsheet: many business users already know how to interpret numbers on one. 1010data takes this idea and expands it exponentially. The company’s software-as-a-service data warehouse provides fast-response queries to datasets that contain hundreds of billions of rows, serving up results via a Web browser into familiar formats including Microsoft Excel.

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By offering its analytics platform in a cloud-based model, 1010data seeks to lower the barrier to entry for IT and business decision-makers who want to get insights from growing datasets but don’t want to invest in high-end database management systems and related hardware, or resources to load and update datasets.

The model has another benefit, said Sandy Steier, 1010data CEO and cofounder. “There’s a philosophy here: to break down the barriers, and allow business users, end users to get at the data in a totally free, open way,” he said. That means making data accessible to more users, without having to wait for analysts to process research requests.

The shopping basket use case: Dollar General, a growing discount retailer with more than 10,000 stores in the U.S., is a marquis customer of 1010data that has used the cloud-based system since 2008 to analyze point-of-sale (POS) transactions and has since broadened its use to examine inventory flow in every store, among other functions.  While Dollar General declined an interview request for this article, the retailer is on record as implementing a market basket project using 1010data to speed its analysis and decision-making.

Representatives from 1010data demonstrated the ways a retailer like Dollar General uses the system—not just internally, but to turn its analytics into a revenue source by creating reports for business partners like consumer packaged goods companies to track the performance of specific goods sold.

Dorje Mar, an analyst for 1010data, showed how a business analyst could use a Web-based interface to filter two-years’ worth of POS data collected into 25 billion rows. A representative from a manufacturer of foot care products, for example, could examine its sales during the previous month to track changes. She could also drill down to view sales by individual products. And she could look at which products were correlated to the biggest shopping baskets in a given time period, the amount of money spent on average during these shopping trips. In each case, the system filtered the results in seconds.

It is routine practice for a 1010data user to save queries like the ones above for repeated use, Mar said. The look and the feel of the interface resembled Excel, though Mar said he was using statistical algorithms more akin to SAS and SPSS BI tools.

In addition to revealing insights about consumer behavior, such reports also open up the chance to create data-driven experiments about product placement and promotions.

About the technology: 1010data’s core technology is a columnar database. In the cloud-based version, the company collects a customer’s datasets and loads them on its servers in a way that segments the data for ease of access. Steier said the company’s technology does optimize its use of memory, but it is not considered an in-memory database like SAP HANA or Oracle Exalytics. “Our algorithms are optimized to deal with data that is not in memory,” he said.   A customer also could load 1010data software onto commodity servers to use on premise.

1010data has a suite of interfaces to BI tools and is working to strengthen and broaden them, Steier said. On September 18, the company announced a partnership with Information Builders to link the company’s WebFocus BI and analytics tools to the 1010 data platform.

Michael Corcoran, chief marketing officer of Information Builders, said in an interview that retail customers of both companies were seeking more business intelligence capabilities to expand their use of the 1010data platform. A benefit of the deal, he said, was “with WebFocus, we get BI out to the non-technical people, to get the data used by as many people as possible.”

Steier said that 1010data hopes to add more capabilities for data visualizations in the future.

Sandy Steier, CEO of 1010data

Sandy Steier, CEO of 1010data

About the company: Launched in 2000, 1010data has its roots in Wall Street. Steier and cofounder Joel Kaplan, 1010data’s chairman and CTO, each worked at UBS North America and Morgan Stanley in leadership research and technology posts. They cite their work as early as 1980 in using columnar databases, parallel and distributed processing techniques to gain competitive edge. Their idea for creating a SaaS offering for cloud-based data analytics predated the terms “Saas” and “cloud,” Steier noted, but it is intended to simplify the front end of crunching large datasets.

The company counts the New York Stock Exchange as its first major customer, and has grown to the retail and manufacturing.

What other say: Technology industry observers say they are impressed with 1010data’s technology, but they suggest the company will face resistance from IT executives at the large companies it targets who may be reluctant to try a new player for a core analytical function.

Gartner analysts, in their vaunted Magic Quadrant for data warehouse and database management systems, place 1010data in the “challengers” section, vying with a familiar roster of market leaders: Teradata, Oracle, IBM, EMC/Greenplum, SAP’s Sybase and Microsoft. Gartner says that in addition to facing off with technology vendors, 1010data also competes with system integrators for customers.

Mark Smith, CEO at Ventana Research, writes, “The immediate challenge for 1010data is to get the market to understand that it offers more than a data warehouse. The platform provides big-data analytics that do not require organizations to learn new technologies but let analysts move beyond silos of spreadsheets and reporting to real analytics. It helps build the foundation to more advanced analytics like predictive analytics.”

Michael Goldberg is editor of Data Informed. Email him at michael.goldberg@wispubs.com.

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