Richard D. Hagedorn Certifications: Summary: • 10 plus years’ experience in HADOOP both development and architecture with 6 plus years as an architect. My initial work included work at Berkeley 2003, on initial release of Hadoop and next with AWS, the Amazon Web Services, Cloudera CDH 5.8, and Hortonworks/Azure. ETL process including scripting 14+ years, Zookeeper, HMaster, HBase database, HFile, Apache: Flume (log files) 2 years, Oozie (sched. Workflow) 1 + year, Sqoop (xfers data) 3 years, Python (2.7 w/SPSS Statistics 23 ) 7 years, Dev Tools such as Spark (with Perf, & Caching) 2 years, HBase 7 years, Pig 4 years, Analysis with: Drill (SQL) 2 years, Hive (HQL) 4 years, Mahout (Clustering, Classification, Collaborative filtering) 6 mos., Performance tuning with Cassandra, Additionally C & C++, and Shell. I have extensive use of MDM tools, and Erwin and additionally power designer and IBM’s ER tool. I have extensive work on Apache Hadoop which is a highly scalable storage platform designed to process very large data sets across hundreds to thousands of computing nodes that operate in parallel. Hadoop provides a cost effective storage solution on commodity hardware for large data volumes with no format requirements. Additionally, extensive work with MapReduce, the programming paradigm that allows for this massive scalability, is the heart of Hadoop. Note that the term MapReduce actually refers to two separate and distinct tasks that Hadoop programs perform. Hadoop has two main components- HDFS and YARN. • Have noticed that some companies are delaying data opportunities because of organizational constraints, others are not sure what distribution to choose, and still others simply can’t find time to mature their big data delivery due to the pressure of day-to-day business needs. With my architect skills and Hadoop I will insure that corporation which adopt Hadoop and its full spectrum of tools won’t leave this opportunity to harness their data on the table; it's a nonnegotiable for that my past clients have been able to pursue new revenue opportunities, beat their competition, and delight their customers with better, faster, analytics and data applications. The smartest Hadoop strategies start with choosing recommended distributions, then maturing the environment with modernized hybrid architectures, and adopting a DATA LAKE strategy based on Hadoop technology. • 25+ years of experience in IT systems or applications development • 15+ years of experience architecting or delivering large scale systems on multiple platforms, with a focus on Big Data Hadoop • Extensive Data Warehousing (Teradata, DB2, Teradata, SQL Server, MySQL & Oracle including building/implementing) • Microsoft Azure Cloud Technologies (Dashbo