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大数据代写 | PSB304IT Big Data Assignment 2

大数据代写 | PSB304IT Big Data Assignment 2

本次美国代写是一个大数据相关的coursework

Task:

Part A (20 marks)

SQL databases are relational and NoSQL are non-relational. This means that NoSQL databases have use
document structure and SQL use table structure. There is a misunderstand that NoSQL databases cannot
store relationship. They just store relationships differently than SQL. When compared with SQL
databases, many find modelling relationship data in NoSQL is easier than in SQ, because related data
doesn’t have to be split between tables. With this in mind, answer the questions below:

1. Create a NoSQL database based on PSB Academy’s operation:

i. Include at least FIVE (5) collections in one database.
ii. You need to fill in all the constraints.
iii. Create relationships between them.

*Show your workings with codes and diagrams.

2. Choose one cloud database and show the step-by-step to create a database.
3. Choose one cloud storage and show the step-by-step to create a storage.

Part B (20 marks)

1. Hadoop is one of the top frameworks in for Big Data. It is having a very widespread
adoption in the industry today. Hadoop processes complex Big Data with its simple to use
tools, providing ease of use for the users. With that, answer the following questions:

i. Choose FIVE (5) tools in Hadoop.
ii. Explain the main functions and how they are used (with diagram).
iii. Explain how they can integrate with each other in the framework.
iv. Explain how the tools can help make Big Data easier to use (discuss about the
interface).
v. Who developed the tool? Include history.

2. Social media analytics is the process of collecting and analysing data from social network
platforms. Social media analytics is used in many fields to understand the trends and
pattern is social media platforms. With that, answer the following question:

i. Find FIVE (5) tool that can do social media analytics.
ii. Explain the main functions and how they are used (with diagram).
iii. Explain how they can help the industries that are using them to make more profit.
iv. Explain how the tools can help make Big Data easier to use (discuss about the
interface).
v. Who developed the tool? Include history.

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