Fremont, CA, January 08, 2014 --(PR.com
)-- This webinar looks at the foundations of data compression in the context of the broader subject of information theory.
The present information age is all about more and more data. The Internet, Big Data, Cloud Computing, and data storage requirements are measured in ever-increasing data. How does the Net handle this near deluge of data? Data compression is being looked at as a solution to counter this ever-expanding flood. But is it trustworthy?
Apart from data safety, there are other multiple and complex issues to be looked at. Are some types of data more compressible than other data? How do the methods of lossless data compression (covered) differ from loss-causing data compression? The speaker will lead participants into a meaningful and perceptive discussion on areas such as lossless compression, its limitations, and the tradeoffs between storage reduction and increased processing required to compact and re-expand data.
The speaker will impart valuable insight into how lossless compression works and why the techniques are robust and trustworthy. The measure of information is defined formally as entropy, a term that Claude Shannon borrowed from quantum mechanics.
This webinar will offer examples of Huffman coding and dictionary methods that fuel the popular dominant methods of Lemple and Ziv. Transform methods, such as the Lemple Ziv Welch, which provide advantages for compressing data with measurable periodicity, will be discussed, as will the closely related to data compression methods and data deduplication, which reduce the overall redundancy across one or more data storage systems.
This session will cover the following topics:
- Entropy as the measure of information
- Shannon's Source Coding Theorem
- Huffman Trees and Huffman Coding
- Arithmetic coding
- Dictionary methods
- Transform methods
- Data deduplication
- Implementation considerations, Open Source software, Hardware compression chips
When: January 28, 2014, 10:00 AM PST | 01:00 PM EST
Dr. Raymond Moberly, a consulting subject matter expert in the field of Information Theory, is knowledgeable about principles of error correction, cryptography, and data compression. He has worked extensively in the field of software defined radio and has led development efforts for embedded software and firmware on microcontrollers, digital signal processors, and field programmable gate arrays.
He has extensive experience in the verification and validation of systems through all development phases including formal qualification testing. He enjoys profiling software in order to analyze and better optimize code performance.
Raymond holds a bachelor's degree in engineering from Caltech, Masters in Applied Mathematics from San Diego State University, and a doctorate in computational science from the Claremont Graduate University.
The webinar will benefit
- System Architects
- Software Developers
- Data Analysts
- Technical Managers
- IT Project Manager
- IT Managers
- Database Administrators
Duration: 90 minutes
To enroll for this webinar, contact