Quantexa Case Studies Leveraging IoT for Analyzing Panama Leaks

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	Leveraging IoT for Analyzing Panama Leaks Quantexa

Leveraging IoT for Analyzing Panama Leaks

Quantexa

Technology Category	Application Infrastructure & Middleware - Data Visualization Cybersecurity & Privacy - Endpoint Security
Applicable Industries	Finance & Insurance Mining
Applicable Functions	Procurement
Use Cases	Time Sensitive Networking
Services	System Integration
Challenge	The Panama Leaks, the largest leak of its kind, revealed how the world's rich and famous were moving and hiding money across the globe. The leak consisted of over 11 million documents showing how money was laundered through offshore accounts and entities. The documents implicated a wide range of individuals, from world leaders to soccer stars. However, the sheer volume of data presented a significant challenge. The documents, dating back to the 70s, included emails, contracts, transcripts, photos, and even passports. The challenge was to mine this massive data set for interesting data points such as people mentioned, organizations, locations, and topics discussed. Read More
About Customer	The customer in this case is AYLIEN, a data analysis company. AYLIEN is a company that is passionate about data and uses world events like the Panama Leaks to showcase their technology and solutions. They are interested in mining large data sets for interesting data points and insights. They have developed a News API that allows them to scan thousands of monitored news sources for articles related to specific topics. The API also has text analysis capabilities that allow them to identify and index key data points in those articles for further analysis. Read More
Solution	AYLIEN, a data analysis company, decided to leverage their News API to mine the reports. They started by building a simple search using their News API to scan thousands of monitored news sources for articles related to the leak. They collected over 4,000 articles which were then indexed automatically using their text analysis capabilities in the News API. This allowed them to identify and index key data points in those articles for further analysis. They focused on keywords, entities, concepts, and topics. They also used the Time Series endpoint in the News API to graph the volume of stories over time, showing how the volume of stories increased as the story spread. They also used the API to extract any mentions of Entities and Concepts in the articles indexed. The main entities they focused on included; keywords, people, organizations, and countries. Read More Log in to view content
Contents

Technology Category

Application Infrastructure & Middleware - Data Visualization

Cybersecurity & Privacy - Endpoint Security

Applicable Industries

Finance & Insurance

Mining

Applicable Functions

Procurement

Use Cases

Time Sensitive Networking

Services

System Integration

Challenge

The Panama Leaks, the largest leak of its kind, revealed how the world's rich and famous were moving and hiding money across the globe. The leak consisted of over 11 million documents showing how money was laundered through offshore accounts and entities. The documents implicated a wide range of individuals, from world leaders to soccer stars. However, the sheer volume of data presented a significant challenge. The documents, dating back to the 70s, included emails, contracts, transcripts, photos, and even passports. The challenge was to mine this massive data set for interesting data points such as people mentioned, organizations, locations, and topics discussed.

About Customer

The customer in this case is AYLIEN, a data analysis company. AYLIEN is a company that is passionate about data and uses world events like the Panama Leaks to showcase their technology and solutions. They are interested in mining large data sets for interesting data points and insights. They have developed a News API that allows them to scan thousands of monitored news sources for articles related to specific topics. The API also has text analysis capabilities that allow them to identify and index key data points in those articles for further analysis.

Solution

AYLIEN, a data analysis company, decided to leverage their News API to mine the reports. They started by building a simple search using their News API to scan thousands of monitored news sources for articles related to the leak. They collected over 4,000 articles which were then indexed automatically using their text analysis capabilities in the News API. This allowed them to identify and index key data points in those articles for further analysis. They focused on keywords, entities, concepts, and topics. They also used the Time Series endpoint in the News API to graph the volume of stories over time, showing how the volume of stories increased as the story spread. They also used the API to extract any mentions of Entities and Concepts in the articles indexed. The main entities they focused on included; keywords, people, organizations, and countries.

Impact #1	The use of the News API allowed AYLIEN to effectively mine a massive data set for interesting data points. They were able to identify and index key data points in the articles for further analysis. This allowed them to gain insights into what was being discussed, which individuals, organizations, and countries were mentioned in the articles, and how often they were mentioned. They were also able to see how the story developed over time, with the volume of stories increasing as the story spread. This analysis provided valuable insights into the Panama Leaks and showcased the capabilities of AYLIEN's technology and solutions.

Impact #1

The use of the News API allowed AYLIEN to effectively mine a massive data set for interesting data points. They were able to identify and index key data points in the articles for further analysis. This allowed them to gain insights into what was being discussed, which individuals, organizations, and countries were mentioned in the articles, and how often they were mentioned. They were also able to see how the story developed over time, with the volume of stories increasing as the story spread. This analysis provided valuable insights into the Panama Leaks and showcased the capabilities of AYLIEN's technology and solutions.

Benefit #1	Over 4,000 articles related to the Panama Leaks were collected and analyzed.
Benefit #2	The data set included over 11 million documents.
Benefit #3	The documents dated back to the 70s, providing a historical perspective on the issue.

Benefit #1

Over 4,000 articles related to the Panama Leaks were collected and analyzed.

Benefit #2

The data set included over 11 million documents.

Benefit #3

The documents dated back to the 70s, providing a historical perspective on the issue.

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Overview

Leveraging IoT for Analyzing Panama Leaks

Operational Impact

Quantitative Benefit