November 14, 2013 - With the avalanche of data about operations, customers, and products, leading companies are utilizing Big Analytics to better understand historical patterns and predict what may come next to create sustained competitive advantage. Dan Mallinger, who leads Think Big Analytic’s data science team, will focus on practical examples of where companies are implementing new analytics approaches over big data.
October 12, 2013 - This talk provides an overview of the open source Storm system for processing Big Data in realtime. The talk starts with an overview of the technology, including key components: Nimbus, Zookeeper, Topology, Tuple, Trident. The presentation then dives into the complex Big Data architecture in which Storm can be integrated. The result is a compelling stack of technologies including integrated Hadoop clusters, MPP, and NoSQL databases.
August 21, 2013 - In a whirlwind of big data tools like MapReduce, NoSQL, Hadoop, and their cousins and brothers, it’s difficult to understand the stack you need to make your data as useful as possible. How do you decide which tools to use, and once you do decide, how do you make the jump?
July 7, 2013 - The SF Data Mining meetup focuses on all aspects of the data pipeline–from data acquisition and big data storage to machine learning and data visualization.
July 2, 2013 - Think Big CEO, Ron Bodkin, discusses what’s driving big data solutions today and how they are creating value for businesses.
April 11, 2013 - Big Data Innovation is the largest gathering of Fortune 500 business executives leading Big Data initiatives. The Summit will help your business understand & utilize data-driven strategies and discover what disciplines will change because of the advent of data.
March 21, 2013 - Join Ann and Ron for a discussion titled, “Analytics at NASDAQ Scale”, which will cover how one of the world’s leading financial exchanges is using Big Data to support business goals.
March 4, 2013 - A connected world, brimming with data and fueled by near-limitless computing power, is changing everything about how we live, love, work, and play. It’s a change that offers tremendous opportunity—to transform business, end corruption, teach the world, and help society tackle its biggest challenges.
February 28, 2013 - O’Reilly’s Strata Conference brings together the leading minds in big data: the decision makers using the power of big data to drive business strategy as well as the practitioners who collect, analyze, and manipulate the data.
February 27, 2013 - Think Big Analytics’ Rick Farnell goes live inside theCUBE with Wikibon’s Jeff Kelly to discuss the role of professional services in Big Data and Hadoop environments. Farnell explains his approach to bridging the IT/Business divide for successful, long-term Big Data deployments.
The breakthrough of internet-enabled devices offers promising solutions for all industries – from consumer to energy to high tech. This talk provides a quick overview of the new enterprise technology stack that is required in order to ingest, sessionize and aggregate the massive amounts of data generated by these devices. We will also discuss Big Data applications that can be built to enable predictive insights and real-time reporting to enable measurable business impact.
Are you prepared for the changes that are happening within the technology services industry? Shifting customer requirements. New business and technology consumption models. The big data explosion. The emergence of Services 2.0. The changes are taking place at great speed, and they have major implications for your services business.
Connected devices are being brought online in the field and onsite, each of them transmitting valuable data. How do energy companies manage the trillions of kilobytes of unstructured data? Collecting, managing and analyzing data using Big Data techniques leads to better business decisions and lasting competitive advantage.
Ron provides an overview of the open source Storm system for processing Big Data in realtime. The talk starts with an overview of the technology, different API options, and discusses integration with messaging systems and databases. It then reviews real world use cases for realtime Big Data analytics and discusses how Storm, Kafka, NoSQL databases, and Hadoop can integrate to provide solutions.
Douglas Moore covers Big Data Analytics applications for Energy Companies. He also goes over the “Imagine” approach of Think Big Analytics.
Discusses dimensionality reduction terms such as SVD, LSA, pLSA and MinHash, including what these terms have in common, how they differ and when it’s appropriate to use which. The course is relevant for modelers, business intelligence and technical developers.
Daniel Eklund presents a survey of various Big Data relational technologies and discusses how to use theory to dissect the newest technology.
Dean Wampler discusses the strengths and weaknesses of MapReduce, and the newer variants for big data processing: Pregel and Storm.
This powerpoint presentation covers an intro to Hadoop and the use of Predictive analytics using Storm, Hadoop, R on AWS.