apa style

In a short paper (2-3 pages), please address each of the topics below with a 2-3 paragraph narrative for each section.

1. Course Content: Describe the most important aspects of this course for you with respect to the content that was covered or activities in which you participated. Discuss the relevance and value or the practicum assignment with respect to your knowledge acquisition.

2. Application of Course Content: Describe how you applied what you learned in this course at your workplace. Discuss how this course may have impacted your specific job, techniques you used at work, or other relevant aspects that show how what you learned was linked to your job.

3. Job Experience Integration: Describe how your work experiences were used in the classroom and attributed to your performance in the course. Discuss how integrating your work experiences in class activities assisted in understanding topics discussed within the course.

Course Description:

You will be introduced to the fundamental concepts of Big Data, explore big data and its implications in solving business problems. Also, you will be introduced to the life cycle of data analytics and will be able to translate business issues and hypothesis into analytical problem statements. Students will be exposed to the technologies commonly used to obtain, munge and prepare data sets. We provide you with insights into how technology transitions in software, hardware, and delivery models are changing the way that data can be used in new ways. Students will also be given a brief overview of data warehousing, data mining and information retrieval.

Course Objectives:

At the conclusion of this course you will be able:

· To understand big data technologies.

· To know the ways that companies are using emerging technologies

· To learn the way that organizations can leverage more data than was possible in the past

· To distinguish what is Big Data (volume, velocity, variety), and will learn where it comes from, and what are the key challenges

· To determine how and where Big Data challenges arise in a number of domains, including social media, transportation, finance, and medicine

· To Investigate multicore challenges and how to engineer around them

· To learn how to maximize the MapReduce programming model: What are its benefits, how it compares to relational systems, and new developments that improve its performance and robustness

· To learn why building secure Big Data systems is so hard and survey recent techniques that help; including learning direct processing on encrypted data, information flow control, auditing, and replay

· To discover user interfaces for Big Data and what makes building them difficult

· To understand the benefits and challenges of open-linked data