Speaker "Dave Mariani" Details Back



BI on Hadoop


Trying to make Hadoop work with your BI tools (Tableau, Excel, Qlik, MicroStrategy, Pentaho...etc?). Join this interactive session and find out how to make it work! Dave Mariani ran Yahoo! data pipelines and analytics teams at the time Hadoop was born. After Yahoo!, he went on to run engineering at Klout, where he managed a 200+ node cluster and Hive Data Warehouse of over one trillion rows. In this session , you will learn: The Gotchas of Big Data: What matters and what's a distraction OLAP on Hadoop: The best architectural options (ROLAP, MOLAP, in-memory) Data Warehouse Design: the benefits of schema on demand vs. schema on load Registered participants will get access to webinar recording on-demand.


Hands on technology executive with 25 years of experience in delivering Big Data, Consumer Internet, Internet advertising and hosted services platforms, creating nearly $600 million of enterprise value. Created the world’s largest data warehouses including a petabyte Hive warehouse at Klout and the world's largest cube at Yahoo!. At Klout, created a social analytics service that includes a consumer and mobile site, Hadoop warehouse and serving infrastructure, a social advertising platform and a public API serving over 30 billion calls per month. As a VP for Yahoo!, managed engineering for audience and advertising data pipelines and analytics ingesting 20TBs of data per day across multiple 4,000 node Hadoop clusters. As CTO for Bluelithium, managed a display advertising network delivering 300M ads per day while delivering a multi-terabyte behavior targeting data warehouse. Drove the sale of the company to Yahoo! for $300M. As CTO of Digital Impact, Inc., delivered an industry leading SAAS online marketing platform and drove its sale to Acxiom Corporation for $140 million. Founded MineShare, Inc and sold it to Digital Impact, Inc. (NASD:DIGI) for $34.4 million. Specialties:Big Data, Internet advertising, mobile, analytics, OLAP, enterprise software Hadoop, Hive, HBase, Scala, Node.js, MongoDB, Oracle, SQL Server