The literal meaning of ‘Big Data’ seems to have developed a myopic understanding in the minds of aspiring big data enthusiasts. When asked people about Big Data, all they know is, ‘It is referred to as massive collection of data which cannot be used for computations unless supplied operated with some unconventional ways’.
Big Data, is not just about, storing and extracting data, but much more than that. Big Data, itself comprises of so many technologies that it is difficult to recall which one to start learning with. No really! Some of the technologies big data consists of is Hadoop, MapReduce, Apache, Pig, Hive, Flume, Sqoop, Zookeeper, Oozie, Spark, Cassandra, Mongo DB and what not!
Companies are desperately in search of skilled big data analysts. Considering the fact, that data is being collected and stored at a velocity faster than ever, the urgency of such skilled professionals increases further.
The explosion of social media and the computerization of every aspect of social and economic activity resulted in creation of large volumes of mostly unstructured data: web logs, videos, speech recordings, photographs, e-mails, Tweets, and similar. In a parallel development, computers keep getting ever more powerful and storage ever cheaper. Today, we have the ability to reliably and cheaply store huge volumes of data, efficiently analyze them, and extract business and socially relevant information. The key objective of this course is to familiarize the students with most important information technologies used in manipulating, storing, and analyzing big data. We will examine the basic tools for statistical analysis, R and Python, and several machine learning algorithms. Students will gain the ability to initiate and design highly scalable systems that can accept, store, and analyze large volumes of unstructured data in batch mode and/or real time.
BSS Diploma in Big Data Analytics Course Eligibility
- 10+2 pass or its equivalent pass with Physics, Chemistry, Biology and Mathematics
BSS Diploma in Big Data Analytics Course Syllabus
Talking about training courses, the syllabus may vary depending on the course level (beginners or advanced). While searching for big data resources, we realized there isn’t a standard syllabus available which is globally recognized. The sequence may differ, depending on the course structure of training provider.With the syllabus mentioned in this article, you should get a brief idea of all big data related technologies and what you should expect from you training provider. The Syllabus of BSS diploma in Big data analytics follows through certain modules mentioned below.
Big Data Analytics Course Content
1) Foundations of Data Science
2) Big Data Technology
3) Computing for Data Analytics
4) Programming for Data Analytics
5) Marketing Analytics
6) Algorithms for advanced Analytics
7) Multivibrate Techniques for Data Analytics
8) Python Programming for Data Analytics
9) Decision Management systems
10) Big Data Security
11) Risk Analytics
12) Information Storage Management
13) Cloud Computing
14) Cluster Computing
15) Functional Programming
16) Web Intelligence and Big Data Analytics
17) Social Network Analytics
18) Streaming Analytics
19) Pattern Recognition Techniques
Typical employers of Big data analysts
Specialist software development companies
Public sector organisations
Social media specialists
Colleges and universities
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