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The project involved a comprehensive analysis of 10 e-commerce stocks, focusing on their trends during the first two weeks of April 23. The key technologies used : AWS(Lambda, Athena, Glue, and EMR,), Python, SQL

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PoulomiTarania/E-commerce-Analysis-using-AWS-components

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E-commerce-Analysis-using-AWS-components

The project involved a comprehensive analysis of 10 e-commerce stocks, focusing on their trends during the first two weeks of April 23. The key technologies used : AWS(Lambda, Athena, Glue, and EMR,), Python, SQL The project was divided into four main components:

1. Data Transformer (Lambda Function):

A Lambda function was employed to gather and transform the data. It facilitated the collection and processing of relevant information from various sources.

2. Data Collector (Kinesis Stream):

A Kinesis stream serves as a repository for the collected data. It provided a scalable and reliable solution for storing and managing the streaming data.

3. Data Analyzer (Serverless Querying with Athena):

The project utilized a serverless process that allowed for efficient querying of data stored in Amazon S3. Athena, as a serverless query service, enabled us to perform in-depth analysis and extract valuable insights from the dataset.

4. Data Visualization:

The final component involved visualizing the results of the data analysis. Various visualization techniques were applied to present the trends, patterns, and volatility of the e-commerce stocks. These visualizations offered a clear and intuitive representation of the findings.

The project's scope extended beyond technical aspects, providing valuable insights into the ecommerce industry. The analysis encompassed prominent e-commerce stocks such as:

Amazon(AMZN), Alibaba Group (BABA), Walmart (WMT), eBay (EBAY), Shopify (SHOP), Target (TGT), Best Buy(BBY), The Home Depot (HD), Costco (COST), and Kroger (KR).

In conclusion, this project showcased the integration of diverse technologies and provided a comprehensive understanding of the selected e-commerce stocks, their volatility, and trends.

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Screenshots:

1. S3 bucket

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2. AWS Kinesis Monitor

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3. AWS Lambda Execution results

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4. Athena results

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Visualizations:

1) Graph the average volatility trend per company. Which company is the most volatile? From the above graph, we can see that Costco appears to be the most volatile

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Based on the graph of the average volatility trend per company, it can be observed that Costco exhibits the highest volatility compared to other companies.

2) Graph the daily highest volatility per company. Do the findings from this graph support your conclusion from the first graph?

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The graph displaying the daily highest volatility per company confirms the earlier conclusion. Costco stands out prominently with significantly higher bars representing its daily highest volatility compared to other companies.

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The project involved a comprehensive analysis of 10 e-commerce stocks, focusing on their trends during the first two weeks of April 23. The key technologies used : AWS(Lambda, Athena, Glue, and EMR,), Python, SQL

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