Big Data Warehousing Meetup: Solving Big Data Challenges in the Cloud (Slides)

The Big Data Solution

At Caserta, we are firm believers in big data thriving on the cloud. The instant-on, nearly unlimited storage and computing capabilities of AWS has made it the defacto solution for a full spectrum of organizations needing to process large amounts of data.

What’s more, an ecosystem of value-added platforms has emerged to further ease and democratize the implementation of cloud based solutions. Qubole has developed a great platform for easily deploying and managing ephemeral and long-lived Hadoop and Spark clusters on AWS.

Moving Past Infrastructure Limitations: Data Warehousing at MediaMath

Over the past year and a half, MediaMath has undertaken a “data liberation” effort in an attempt to leave their bigbox, monolithic data warehouse behind. During Caserta’s Big Data Warehousing talk, Rory Sawyer, Software Engineer at MediaMath, described how this effort transformed MediaMath’s legacy architecture and legacy mindset, which imposed harsh inefficiencies on data sharing and utilization. The current mindset removes these inefficiencies and allows them to say “yes” to more projects and ideas.

Rory also demonstrated how MediaMath uses Amazon Web Services and Qubole so that infrastructure is no longer a limiting factor on what and how users query. This combination allows them to scale their resources up and down as needed while bridging different data sources and execution engines. Using and extending MediaMath’s data warehousing is no longer a privileged activity but an ability that every employee and client has.

The following presentations were given at a Big Data Warehousing Meetup with Caserta, MediaMath and Qubole.