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Summary:

We have chosen eight of our favorite startups from 2013 as winners of the inaugural Gigaom Structure Data Awards, but readers will also have their chance to vote for the Readers’ Choice awards.

SD awards

Data is taking over the world, which makes for an exciting time to be covering information technology. Almost every new company understands the importance of analyzing data, and many of their products — from fertility apps to stream-processing engines — are based on this understanding. Whether it’s helping users do new things or just do the same old things better, data analysis really is changing the enterprise and consumer technology spaces, and the world, in general.

With that in mind, we have decided to honor some of the most-promising, innovative and useful data-based startups with our inaugural Structure Data awards. The criteria were simple. Companies (or projects) must have launched in 2013; must have been covered in Gigaom; and, most importantly, must make the collection and analysis of data a key part of the user experience. Identifying these companies was the easy part; the hard part was paring down the list of categories and candidates to a reasonable number.

Here are the Gigaom Editor’s Choice winners. A founding member of each company will take the stage at Structure Data on March 19, in New York, to talk more about the vision behind their companies:

  • Machine Learning/Artificial Intelligence: Ayasdi. Ayasdi’s topological data analysis technology analyzes and visualizes large, complex data sets so experts can focus their energy on investigating correlations rather than on finding them.
  • Infrastructure: DatabricksDatabricks was created to commercialize Spark, a data-processing framework designed to be much faster and easier than Hadoop MapReduce. Its founding team helped build Spark at the University of California, Berkeley.
  • Business Analytics: PaxataPaxata was built with the idea of making data analysis easier by making it easier to get to that point. Its algorithms help automate the process of cleaning and formatting raw data so it’s ready for analytic software.
  • Individual Analytics: PlaidPlaid wants to free statement data from banks and make it available to developers via API. This means companies can automate certain accounting operations, and consumers can get a new way of interacting with their spending.
  • Industry Application: Premise DataPremise Data is trying to determine economic stability and consumer activity in emerging markets. Its network of workers take smartphone photos which are analyzed to extract key pieces of information.
  • Project/Free Service: ScraperWikiScraperWiki didn’t launch in 2013, but the company had something of a rebirth last year and exposed some of its web-scraping capabilities (e.g, collecting data from Twitter) as free services designed for even non-coders.
  • Text Analysis: IdibonIdibon wants to deliver natural language processing via API for things like sentiment analysis and categorization, but also to do it globally. The company’s platform currently can analyze text in 50 languages.
  • Back-office Application: SpinnakrSpinnakr is trying to do web analytics for the predictive world. Rather than just show users traffic activity, its application tells where traffic is coming from, what it means and how customers might act upon it.

But we want your input, too. Please vote here for the Structure Data Readers’ Choice awards. Voting will close on February 14th, and winners will be announced on February 18th. Winners will receive a free ticket to the event along with other perks.

  1. Plaid sounds very interesting.. think it could have an impact on banking consumers but financial services, notorious for their high entry barriers could hurt Plaid’s prospects. Wish there were a way to go direct to users and not go the enterprise route.

    Data-fyed
    NYC

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