Big Data Introduction to Big Data, Hadoop and Spark Agenda About speaker and itversity Categorization of enterprise applications Typical data integration architecture Challenges with conventional technologies Big Data eco system Data Storage - Distributed file system and databases Data Processing - Distributed computing frameworks Data Ingestion - Open source tools Data Visualization - BI tools as well as custom Role of Apache and other companies Different Certifications in Big Data Resources for deep dive into Big Data Job roles in Big Data About me IT Professional with 13+ years of experience in vast array of technologies including Oracle, Java/J2EE, Data Warehousing, ETL, BI as well as Big Data Website: http://www.itversity.com YouTube: https://www.youtube.com/c/itversityin LinkedIn Profile: https://in.linkedin.com/in/durga0gadiraju Facebook: https://www.facebook.com/itversity Twitter: https://twitter.com/itversity Google Plus: https://plus.google.com/+itversityin Github: https://github.com/dgadiraju Meetup: https://www.meetup.com/Hyderabad-Technology-Meetup/ (local hyderabad meetup) https://www.meetup.com/itversityin/ (typically online) Categorization of Enterprise applications Customer Analytics Enterprise applications Operational Decision Support Traditionally enterprise applications can be broadly categorized into Operational and Decision support systems. Lately new set of applications such as Customer Analytics is gaining momentum (eg: YouTube Channel for different categories of users) Enterprise Applications Most of the traditional applications are considered monolith (n-tier architecture) Monoliths are typically built on RDBMS databases such as Oracle Modern applications use micro services and considered to be polyglot Now we have choice of different types of databases (we will see later) Enterprise applications Take the example use case (eCommerce platform) Operational Transac

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