Discover the Best Big Data Computing Assignment 6 Answers

Big Data Computing Assignment 6 Answers: Insights and Examples You Need to Know

Data science and analytics are fast-growing fields in the current digital era. The prevalence of big data makes it necessary to have professionals who can analyze, interpret and draw conclusions from it. As a Big Data Computing student, you understand the importance of completing Assignment 6 to perfect your skills in big data computing. In this article, we will delve into the best Big Data Computing Assignment 6 answers, including insights and examples that will help you score well.

What is Big Data?

The term Big Data refers to extremely large data sets that are complex and cannot be analyzed through traditional data processing. It encompasses structured, semi-structured, and unstructured data that can be analyzed computationally to reveal insights, trends, and patterns. The high volumes of big data require specialized tools and techniques to extract valuable information from it.

Big Data Computing Assignment 6

To complete Big Data Computing Assignment 6, you will need to demonstrate your understanding and skills in various aspects of big data computing, including data cleaning, filtering, manipulation, and analysis. The assignment comes with various questions that require you to apply different programming languages, including R, Python, and Hadoop. Your answer should be well-structured, providing detailed explanations, and showing the approach you used to come up with the final output.

Sample Answer of Big Data Computing Assignment 6

Question 1: Clean and filter the data in R.

To clean and filter data in R, you will need to use the dplyr package. The following steps can be followed to achieve this:

1. Load the dplyr library using the ‘library(dplyr)’ command.
2. Read the data by using the ‘read.csv(‘filename.csv’)’ command.
3. Filter the data using the ‘filter()’ command. For instance, to extract data with missing values, you can use the command ‘filter(is.na(data))’.
4. Clean the data using the ‘na.omit()’ command to remove missing values.

Question 2: Manipulate data in Python

To manipulate data in Python, you will need to use the pandas library. The following are the steps you should take:

1. Import the pandas library using the ‘import pandas as pd’ command
2. Read the data by using the ‘pd.read_csv(‘filename.csv’)’ command
3. Manipulate the data by using the various pandas functions, such as ‘groupby’, ‘merge’, ‘pivot_table’, and ‘apply’.

Question 3: Analyze Data in Hadoop

To analyze data in Hadoop, you will need to use the MapReduce paradigm. The following are the steps you should take:

1. Load the data into the Hadoop Distributed File System (HDFS) using the ‘hadoop fs -put’ command.
2. Write a MapReduce program that performs the analysis you require.
3. Execute the MapReduce program using the ‘hadoop jar’ command.

Conclusion

Completing Big Data Computing Assignment 6 requires an in-depth understanding of big data computing and specialized tools and techniques to manipulate, clean, and analyze data. You need to be detail-oriented, follow instructions, and demonstrate your problem-solving skills to score high in the assignment. The above insights and examples should guide you towards producing the best Big Data Computing Assignment 6 answers that will earn you a good score. Remember to organize your work logically, provide detailed explanations, and show all your working.

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