Page 101 - Data Science class 11
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ethics in data science
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Learning outcome
1.1 What is Data Ecosystem?
1.2 How to Fast-track Data Ecosystems
1.3 How Data Ecosystem is Evolving
1.4 Why do Data Scientists need to Understand Ethics?
1.5 Insider and Outsider Threats
1.6 Real Life Cases of Insider Attacks
1.7 Cyber Attacks
1.8 Security Checkup
1.9 What is Data Governance Framework?
In the previous class, you have already learnt about ethical guidelines and data governance frameworks in data
science. In this chapter, you will learn more about ethical guidelines and data governance frameworks.
1.1 What is Data EcosystEm?
The term Data Ecosystem is defined as a platform used by an organisation to collect, store, analyze and control
data. It is a combination of algorithms, programming languages, packages, cloud-computing services, and general
infrastructure. It helps companies to understand their customers and to make better pricing, operations, and marketing
decisions. However, almost each organisation has a unique data ecosystem. In some cases, when the sources of data
are public or any third-party data providers are leveraged, these data ecosystems may have some similarities. The
term ecosystem is used in place of ‘environment’ because, like real ecosystems, data ecosystems are intended to
evolve over time.
The three main ways in which Data Ecosystems provide value to the companies are as follows:
• Growth: Data ecosystems allow firms to pursue new business opportunities by extending their core business or even
enable completely new products. For example, credit-card processors have created strategic insights on customer
shopping journeys and buying details that they provide with retailers and brands.
• Productivity: Data ecosystems help firms improve operations. Online travel portals that offer insights into customer
behaviour can help airlines and hotels plan for demand and adjust the pricing based on demand.
• Risk reduction: Data ecosystems are crucial in reducing risk, especially for industry groups in which every member
contributes data. For example, pool data to identify fraudulent transactions and accounts in banks.
Ethics in Data Science 99

