Storage, retrieval, analysis, and knowledge discovery using Big Data has made significant inroads in several domains in industry, research, and academia. In my course guide, it will look at the dominant software systems and algorithms for coping with Big Data. Topics covered include large-scale non-traditional data storage frameworks including graph, key-value, and column-family storage systems; data stream analysis algorithms; large scale anomaly detection; information diffusion; and recommendation algorithms.
Topics Covered in my materials
- Polyglot persistence
- Key-value storage systems
- Column-family storage systems
- Graph storage systems
- Algorithms for detecting similar items
- Recommendation systems
- Data stream analysis algorithms
- Link Analysis algorithms
- Clustering algorithms
- Detecting frequent items
About me:
I am a MS CS graduate student from Arizona State University, and I am currently working as a Data Scientist in a MNC in USA working on Hadoop Map Reduce. My course materials will contain every single detail that you will need to master Big Data, it also includes the Google, Amazon, Facebook(Cassandra) file systems along with entire framework of Hadoop and Map Reduce which is a great boom in the current market.
Also, I am also ready to answer any doubts either through mail/telephone you encounter while studying the materials.
Rest assured reading my course materials is all you need to get a great boost in the field of Big Data.
Hear from you soon