Examining GoodData Open Analytics Platform

KDnuggets examines the main features of GoodData Open Analytics Platform, its users, how it compares to competition, and future plans.

By Gregory Piatetsky, Apr 16, 2014.

I recently had a chance to talk to GoodData GoodData about their Open Analytics Platform.

GoodData was founded by Roman Stanek in 2007 in Prague, but is now based in San Francisco, CA. It received over $75M in funding, some from very well-known people or VCs, including Angel funding round with Tim O'Reilly and Ester Dyson, and later funding from VC firm Andreessen Horowitz.

GoodData claims over 130,000 global users for its cloud-based business intelligence platform.

It recently released to good reviews its GoodData Open Analytics Platform, with 5 main components for collecting, storing, combining, analyzing and visualizing data.

GP: Who are the intended users for GoodData Open Analytics Platform?

GoodData's Open Analytics Platform serves both IT on the data governance side and line of business on the data discovery side. By allowing GoodData to own the problem of collecting, storing, and combining data, IT can uplevel their own work to and save time for more valuable efforts. Similarly, GoodData offers an intuitive front-end interface for business users to conduct data discovery, reporting, visualization, and ad hoc analysis--anywhere, anytime.

GoodData dashboard

GP: Can you give us approximate breakdown of your current users (30,000+ companies) by industry?

The breakdown of our current users by industry (in 2013) by Vertical Markets is
  • Communications, Media, and Services 40%
  • Retail 15%
  • Banking and Securities 5%
  • Education 5%
  • Government 5%
  • Healthcare Providers 5%
  • Insurance 5%
  • Manufacturing and Natural Resources 5%
  • Transportation 5%
  • Utilities 5%
  • Wholesale Trade 5%

GP: How do you differentiate yourself from competitors like Alpine Data, BigML, Skytree ?

Those companies focus on enabling end users with data science tools and machine learning, leaving the process of building data models to the customer. GoodData, on the other hand, manages the data modeling process for the customer, in addition to data storage, collection, combination, and preparation, and also provides the end user with intuitive front end data discovery tools so they can gain insight from the data quickly.

This hides the complexity from the end user and allows them to focus on business critical problems rather than managing and organizing data. Additionally, with the Open Analytics Platform customers have the ability to build their own models on top of our platform if they require additional customization or flexibility.

GP: What are the most popular connectors and APIs provided by GoodData?

The most popular connectors and APIs provided by GoodData include the Salesforce Connector, Ruby API for automating common tasks like KPI event notifications, and the suite of APIs for the data connectors.

GP: What functions are provided in GoodData Analytics Engine (XAE) ? Which functions are most used?

GoodData's Analytics Engine supports the process of data combination, and with no-cube technology, allows for flexible slice-and-dice functionality. The engine functions with multi-level caching for exceptional performance, provides dashboards, reports and metrics abstracted from the underlying data model, and is extensible with additional predictive analytics and other advanced modules.

GP: What is your pricing model?

GoodData's pricing model is subscription based. Pricing starts at $2500 per project and the data and user volume affects the final numbers.

GP: What are your plans for next features / solutions to add?

We plan to continue expanding the suite of predictive and analytic functions, grow data discovery and continue to build out the back end infrastructure to provide most the dependable and scalable cloud performance.

Learn more at www.gooddata.com/