March 24, 2015 - In the fast paced and ever changing landscape of Hadoop based data lakes, there tends to be varying definitions of what constitutes a data lake and how they should be used for business benefit—especially in leveraging data science. In today’s webinar, Think Big will share their perspective on Hadoop data lakes from their many consulting engagements.
October 3, 2014 - Over 70 percent of data centers are attacked each year. Risk in today’s complex financial IT environments is a growing concern and comes in many forms, ranging from security and technology risk in operations centers to market and portfolio risk in trading systems. Increasingly, threats and breaches require effective real-time responses to limit potentially severe damage to brand reputation and crippling financial losses.
November 21, 2013 - The Python language combines human-friendly syntax, awesome libraries, and computational chops into one of the most powerful languages in the world today. This webinar provides practical tips for how to leverage Python in your data science projects.
August 29, 2013 - Technology innovates faster than some companies can keep up with, but not Kantar Media. Join us for this webinar as Will Rompala, VP Product Technology at Kantar Media, walks through his Big Data project that transformed one of Kantar’s older portfolio products into a new offering that is relevant and necessary for today’s demands. Will will discuss the business need, the challenges and the solution for how he started his Big Data journey.
August 22, 2013 - Big Data can transform your business but missteps can stall a project. Please join Douglas Moore for this webinar on how to get started on the right foot through proper planning, data selection and setting up a pilot system using Think Big’s Jumpstart program.
July 11, 2013 - What relational languages lack in Turing-completeness they make up for in ease and scalability. That’s why languages like SQL and Pig have come to dominate the data world. This short webinar will give an overview ofrelational algebra - the theoretical framework underlyingrelational languages – and illustrate by example in Pig.
June 13, 2013 - Device data is everywhere. On our phones, energy meters, medical devices, hard drives, routers, and more. Just gathering and storing this data can be a very difficult big data challenge in itself. Join Ryan in this discussion about the typical needs of customers with device data and how Think Big uses technologies like Hadoop, Cassandra, HBase, and Solr to bring real time search to Big Data.
April 26, 2013 - Devices are generating invaluable data that should be captured and analyzed in order to gain consumer insight, predict failure and improve operational efficiencies. Join us for this webinar and hear examples of how to combine device data analytics with new or existing data sets to exceed business goals.
April 18, 2013 - This 45 minute webinar defines Dimensionality Reduction and how it can benefit you in certain situations. We will also discuss 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.
March 21, 2013 - This presentation will give a quick refresher on Storm concepts, however most of the time will be spent discussing a recent project where Storm was a critical part of implementing a predictive analytics use case for an actual customer. Douglas Moore will cover lessons learned, best practices, technical overview of the use case (Storm, Hadoop, EMR and R) and more.
March 14, 2013 - This webinar provides an overview of H Base, how to set up an H Base cluster on EMR, sample code and more. You’ll learn about optimal conditions for H Base and also about Amazon Web Services’ EMR offering.
February 21, 2013 - This webinar discusses the essentials of a Big Data architecture and how technologies are being used to influence different decisions. We will also discuss the skills and processes required to make a successful implementation work.
February 14, 2013 - Consumer habits change fast. So, providing a great customer experience means that your marketing campaigns, apps, and sites must change fast too. Unfortunately, marketing teams, advertising technology companies, and marketing agencies are often constrained by long IT lead times, out-of-date software, and high costs.
February 13, 2013 - Please join Ron Bodkin, CEO of Think Big, in a discussion about how leading technology companies are using Big Data to stay ahead of the competition and exceed their business goals. Ron will discuss real-world use cases, including the new technologies and techniques that were used to generate the desired results.
February 07, 2013 - Dean Wampler, Ph.D., Principal Consultant at Think Big and the co-author of Programming Hive, will discuss several Hive techniques for managing your data effectively and optimizing the performance of your queries.
January 24, 2013 - R and Hadoop are changing the way organizations manage and utilize big data. Join us as Jeffrey Breen explains the core technology concepts and illustrates how to utilize R and Revolution Analytics’ RevoR in Hadoop environments.
January 21, 2013 - Google, Yahoo, and Facebook are well known for their investments in big data. These amazing leaders use a platform called Hadoop to create value from the petabytes of data they are gathering. In this webinar, you will learn about Hadoop and how you can find the best use case for your own big data project.
January 17, 2013 - Jeff Kelly is Principal Researcher at Wikibon and has deep experience in big data, business analytics and data management. He tops Forbes list of “Top Influencers in Big Data” and we invite you to join Jeff in a discussion about the business value of using technologies like Hadoop and MapReduce.
November 16, 2012 - This webinar covers how customers use AWS to build Big Data and Big Analytics solutions. Included in this conversation are case studies of financial services companies using Big Data today.