ANALYTICS & DATA SCIENCE
BIG DATA CONSULTING
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
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