Big Data: Jumpstart Your Career!
Businesses are facing challenges in managing exponential growth of data captured from various sources such as social media, transactional systems, call centers, emails, surveys, etc. More importantly, challenges lie in analyzing and processing information that is disconnected and predominantly unstructured in nature.
Big Data technology emerged to address the challenges in data management and processing of large volumes of non-traditional data using commodity hardware and massive parallelism, and enables companies to gain business insights to drive growth in ways that simply was not possible earlier.
We will start with exploring Big Data from 100K ft view, then zoom into Hadoop fundamental @25K ft view, and finally explore the demo @ground level view.
* Big Data Concepts (100K ft view)
- Why Big Data?
- What is Big data?
What makes Big Data “Big” (Dimensions, the 4V’s)
Big Data Trade-offs (CAP Theorem, BASE Vs ACID, …)
- Big Data Technology Maturity
* How Companies are using Big Data
- Companies and usage examples
* Big Data Business Process
* Big Data Solution Landscape
* Big Data Architecture (75K ft view)
* Big Data Platforms (50K ft view)
- Platform Varities
- Hadoop Momentum
- Hadoop Ecosystem
* Hadoop Platform (25K ft view)
* Hadoop Core (15K ft view)
* Hadoop Sub-projects
* Demo (Ground Zero)
About the Speakers
Anand Vallamsetla is an Architecture Team Lead at a financial institution in Austin area. He is also the Co-founder and CTO of a technology startup company based in India. He has 15 years of experience in leading teams, architecting and building enterprise class applications. He is passionate about emerging technologies and their potential in helping businesses. He also actively contributes to open-source libraries/frameworks.
Krishna Margam is an Enterprise Architect at a financial institution and assists business and IT areas with planning and executing major initiatives. He has 20 years of experience providing consulting services to many companies around the world. His areas of expertise include Enterprise Data Warehousing, Distributed Computing on Massively Parallel Processor based architectures, JEE, Portals, Enterprise Content Management, Identity and Access Management, Master data management and Mainframe technologies. Big Data and NoSQL are an area of his current focus.