ANALYTICS & DATA SCIENCE

We help organizations make better decisions using analytics on Spark and Hadoop

 

Everyone seems to be talking about Apache Spark for big data analytics on Hadoop. However, while Spark has plenty of buzz, there are still growing pains around this nascent technology. To succeed in using Spark for analytics, you’ll need to work with a partner that has the right skills, experience, and approach to make your implementation a success.

 

The world’s first and leading pure-play big data services firm, Think Big helps companies build new business capabilities from running analytics on big data technologies such as Spark and Hadoop. Our #1 goal is to help make YOU effective by providing training (via our Think Big Academy), having our data scientists working side-by-side with your team on data profiling, analysis and modeling. We also advise on best practices we’ve captured from big data engagements.  In fact, we go beyond just helping you use various data science libraries (such as Spark’s MLlib) and other tools to turn new ideas and opportunities into scalable and production-ready solutions.

 

Think Big Data Science service offers:

  • Data Science Assessment –reviews current capabilities and makes recommendations for tools, teams, operating model and governance.
  • Proof of Concept – gathers insights from experiments and link those insights to current business challenges.
  • Implementation – operationalizes use case/s by inserting models and visualizations into production
  • Data Science as a Service – maintains and upgrades previously built models. Updates business with new patterns and insights

 

Data Science on Spark

 

Think Big specializes in big and high velocity data using our experienced consultants to provide predictive analytics for clickstream, Internet of Things, customer insights, content recommendations and more. As companies explore the value of Spark, Think Big has developed a “Spark Readiness Assessment” service to help align program goals with technology capabilities, provide a gap analysis of needed skills and processes, and recommendations to meet your big data objectives with Spark.

 


A proven approach

What’s different about Think Big’s approach to data science?

  • Collaboration, agility and creativity – we’re focused on helping you identify high-value use cases that help you take the lead or close the gap with competitors
  • Partnership – we join your existing teams to drive business outcomes
  • Holistic and inclusive – with a bias toward integrating existing data sets and tools into advanced solutions such as Spark
  • Tested and repeatable – we utilize pre-built components and quality templates for integration and data access
  • Results-driven – mapping existing and new technology assets to specific business goals

 

Visit this link to see our entire portfolio of Spark services.

Think Big Expands Capabilities for Building Data Lakes with Apache Spark

We’re expanding our data lake and managed service offerings using Apache Spark.

Introducing Apache Spark to Your Big Data Architecture

Integrating Apache Spark into your broader analytic ecosystem brings new challenges such architectural-fit, skill set development, adoption, and measurement of business benefits. View this webinar to discover more about Apache Spark from Cloudera & Think Big, a Teradata company experts.

Igniting Analytics with Apache Spark

Interest in Apache Spark is quickly rising as word spreads about the number of advantages it offers. Watch this webinar to examine real-world case studies, and how to integrate Spark with a broader analytic ecosystem.

What Should Apache Spark Mean to Your Business?

Spark is a powerful technology, but in order to see whether Spark is a good fit, you must first know what Spark is and whether you should use it at all.

3 Reasons Why People, Not Robots Are Key to Data Science

In the world of data science, great strides are being made in the area of deep learning. We’ve made so much progress that it is easy to think that instead of having to embrace data science as a discipline, we can have a Watson-like box to perform all of these tasks for us. If you think this way, you are going to miss the boat.