Slideshow 10 More Big Data Companies You Might Not Know

  • March 27 2014, 5:00am EDT
13 Images Total


Where: Redmond, WA What: Tracks and analyzes activity across the customer life cycle. The company’s customer data platform is provided as a cloud-based service, eliminating the need for separate, disconnected point solutions and homegrown analytic tools. How: Captures and analyzes every interaction with every customer — more than 1 billion events per day. Why: Provides the means to answer questions such as which campaigns resulted in the highest lifetime value customers and how does the time of day affect which products sell the best. Of Interest: The Appuri SaaS solution can be deployed quickly — the company claims to be able to have it up and running in 15 minutes.

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Where: Bangalore, India What: Utilizes big data to provide customer intelligence, price optimization, risk management, operations planning and sales and marketing insights. How: Applies proprietary data mining algorithms and machine learning techniques to big-data based problem solving. Why: Big data can be used to generate actionable insights and make better informed, data-driven decisions. Of Interest: Converts large amounts of data into useful information, generating insights by uncovering hidden patterns.

Fractal Analytics Inc.

Where: Mumbai, India What: Uses data analytics to help companies better understand, predict and influence consumer behavior. How: Allows clients to enhance their data analytics functions through outsourcing, instead of having to develop and support these capabilities in house. Why: Analytics allows companies to identify new market opportunities as they emerge, providing them with a first-to-market competitive advantage. Of Interest: Offers a combination of proprietary data mapping, predictive analytics and visualization tools available in a variety of services.


Where: Gurgaon, India What: The big data division of Xebia group, GoDataDriven provides online retail solutions, services and training in Hadoop and related big data technologies for retailers. How: Solutions encompass a combination of big data warehousing, scalable ETL, high-volume data analytics, event processing and analysis. Why: Helps online retailers achieve greater one-to-one customer personalization and interaction. Of Interest: Offers a recommendation engine, extended search capabilities, web-page content display optimization (multi-armed bandit testing), customer behavior analytics and dashboards.

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Where: Toronto, Canada What: Infobright’s Knowledge Grid architecture supports the Internet of Things with a high performance analytic database. How: The database is designed to rapidly analyze machine generated data, enabling applications to perform interactive, complex queries. Why: These queries and their outcomes can lead to faster business decisions and lower data management costs. Of Interest: The Knowledge Grid architecture improves data compression at ratios of 10:1 to 40:1; scales to hold petabytes of historical data for long-term analytics; offers load speeds of terabytes per hour to support real-time query processing and alerting.

Metric Insights

Where: San Francisco, CA What: Provides a Push Intelligence platform that alerts the user when and why key business metrics have changed. How: Connects its KPI Warehouse to metrics from all of the business intelligence, SaaS, big data and data visualization tools used by the customer. Why: Push Intelligence bridges the gap between BI and big data, providing a personalized experience by automatically monitoring key changes in the metrics that are important to each individual user. Of Interest: Metric Insights extends BI beyond the executive suite. It makes it cost effective to share big data with all employees, partners, customers and providers, empowering the entire corporate eco-system to make informed decisions.


Where: Lake Forest, CA What: Designs energy efficient, high density, easy to manage servers for all big data applications. How: Develops server platforms designed for big data applications including Hadoop, Cassandra and MongoDB. Why: Server design offers extreme density and performance with the lowest possible power consumption. One 42U rack unit can hold up to 2 petabytes of storage using just 5 watts per terabyte. Of Interest: The company states its servers consume nearly 60 percent less power and generate 40 percent less heat than other manufacturers.

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Scientel Information Technology

Where: Bingham Farms, MI What: Offers big data analytics, software, hardware, systems design and development and e-commerce solutions. How: Provides three products: DBIS Intranet – an interactive, Web-like wholesale distribution system; DBIS e-Commerce – a business transaction module; and Business Intelligence/analytics – an information analysis tool for making informed decisions. Why: The Scientel platform addresses all big data information management tasks for commercial, scientific and government organizations. It manages structured and unstructured, transactional and non–transactional, indexed and non-indexed data types. Of Interest: Once analyzed, data can be presented in relational, hierarchical, network, vertical and column schema formats.


Where: San Jose, CA What: Provides enterprise-grade machine learning — a variant of predictive analytics designed for high accuracy at extreme speed and scale. How: The company claims its flagship product, the Skytree Server, is the only general purpose scalable machine learning system on the market. Why: The Machine Learning platform provides deep analytic insights to predict future trends, make business decisions and identify untapped markets and customers. Of Interest: Skytree’s name refers to the cosmic tree of knowledge found in many mythologies, a reference to its mission to bring state of the art research from lab to enterprise. In addition, Skytree data scientists have roots in large scale astronomical data analysis and advanced data structures.

Think Big Analytics

Where: Mountain View, CA What: Provides data science, engineering and training services to help companies meet business goals. How: Think Big specialists identify and prioritize the best opportunities for big data projects based on the client’s desired business outcomes. We then assemble the right architecture and custom applications that create real value. Why: Projects are designed to improve customer service, enhance product offerings and increase operational efficiencies. Think Big claims clients begin to see ROI within the first 40 days. Of Interest: The Think Big Academy offers hands-on training courses and side-by-side mentoring from highly regarded experts, authors and academics. Private and public courses cover technologies, tools and techniques involved in big data implementations, including R, Hadoop, Elastic Map Reduce, H Base and Storm.

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