SOURCE: Trifacta


December 09, 2014 09:00 ET

Webinar - December 11, 2014: Trifacta and Ovum to Discuss Data Wrangling for Agile Analytics

Trifacta CTO, Sean Kandel, and Ovum Analyst, Tony Baer, Illustrate How to Successfully Utilize Exploratory Analytics on Hadoop

SAN FRANCISCO, CA--(Marketwired - Dec 9, 2014) - Trifacta, a leading Data Transformation Platform provider, today announced that Trifacta's co-founder and chief technology officer, Sean Kandel, and Ovum principal analyst, Tony Baer, will present a webinar on how to successfully utilize exploratory analytics on December 11, 2014. The discussion will cover how data wrangling can play a critical role in successfully leveraging Hadoop's schema flexibility to perform exploratory analytics on data of all shapes and sizes.

"Where traditional reporting and analytics deal with structured, cleansed views of data, exploratory analytics requires working directly with raw data of varying structures and formats. Giving users the ability to quickly gain an understanding of the content and analytic potential of these raw data sets in Hadoop is critical to the overall success of exploratory analytics. At Trifacta, our approach leverages a unique combination of data visualization and machine learning to make the process of wrangling this data as agile and productive as possible," said Sean Kandel, chief technical officer of Trifacta.

Kandel's research at Stanford University was focused on user interfaces for database systems and included the development of new tools for data transformation and discovery, such as Data Wrangler. His research involved a study comprised of interviews of numerous data analysts from over 25 organizations across a variety of sectors. Kandel's study found that data analysts spend as much as 80 percent of their time preparing and transforming data, a finding that led to the creation of the Trifacta Data Transformation Platform.

"The ability to explore the data before diving into the analysis process is incredibly valuable. Understanding where to start exploring data poses one of the biggest hurdles to business users of big data analytics. With schema-on-read, a heavy burden is placed on end users who otherwise would be at a loss on how to correlate and transform data," said Tony Baer, principal analyst of Ovum. "With these new challenges, users will need the assist that machine learning-enhanced approaches can provide to get a simpler, Google-like autocomplete to help them transform big data down into an understandable state."

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About Trifacta
Trifacta, the pioneer in data transformation, significantly enhances the value of an enterprise's big data by enabling users to easily transform raw, complex data into clean and structured formats for analysis. Leveraging decades of innovative work in human-computer interaction, scalable data management and machine learning, Trifacta's unique technology creates a partnership between user and machine, with each side learning from the other and becoming smarter with experience. Trifacta is backed by Accel Partners, Greylock Partners and Ignition Partners.

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