Forget about the fake news; data and analytics in politics is what drives elections. John Thuma shares ethical dilemmas he faced while proposing analytical solutions to the RNC and DNC. Not only did he help causes he disagreed with, but he also armed politicians with real-time data to manipulate voters.

Mauricio Aristizabal shares lessons learned from migrating Impact's traditional ETL platform to a real-time platform on Hadoop (leveraging the full Cloudera EDH stack). Mauricio also discusses the company's data lake in HBase, Spark Streaming jobs (with Spark SQL), using Kudu for "fast data" BI queries, and using Kafka's data bus for loose coupling between components.

Francesco Mucio tells the story of how Zalando went from an old-school BI company to an AI-driven company built on a solid data platform. Along the way, he shares what Zalando learned in the process and the challenges that still lie ahead.

If your goal is to provide data to an analyst rather than a data scientist, whats the best way to deliver analytics? There are 70+ BI tools in the market and a dozen or more SQL- or OLAP-on-Hadoop open source projects. Mark Madsen and Shant Hovsepian discuss the trade-offs between a number of architectures that provide self-service access to data.

There are a number of tools that make it easy to implement a data lake. However, most lack the essential features that prevent your data lake from turning into a data swamp. Naghman Waheed and Brian Arnold offer an overview of Monsanto's Data Historian platform, which can ingest, store, and access datasets without compromising ease of use, governance, or security.

There are 70+ BI tools in the market and a dozen or more SQL- or OLAP-on-Hadoop open source projects. Mark Madsen and Shant Hovsepian outline the trade-offs between a number of architectures that provide self-service access to data and discuss the pros and cons of architectures, deployment strategies, and examples of BI on big data.

As organizations look to scale their analytics capability, the need to grow beyond a traditional data warehouse becomes critical, and cloud-based solutions allow more flexibility while being more cost efficient. Billy Liu offers an overview of Kyligence Cloud, a managed Apache Kylin online service designed to speed up mission-critical analytics at web scale for big data.