Selling your Data to the Highest Bidder: Ethics in Data
Learn how Data Ethics and Governance effect our modern world in Data Analytics and what you can do to protect yourself and others.
You’ve heard it before, data is the new oil. Data is fueling decisions, innovation, and business strategies across industries. But with all its power comes a huge responsibility: we need to handle it ethically and govern it properly.
Data is actual power in this day and age, Facebook and other companies sell your data to the highest bidder. They they can use that data for what ever they see fit (most of the time).
And yes, most of us agree to sell our data because anytime we sign up for a new app or account that annoying little box pops up that asks use to “agree with our policy”.
I mean come on, who actually spends the time to read that stuff anyways, most of us just tap yes so we can get on with the actual use of the app or site.
Many times tucked away deep in those “policies” or “agreements” there is some hidden information about a third party using our data. That brings us to the topic here today… ethics.
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That’s why Data Ethics and Governance are critical parts of any data analytics process. They make sure data is used responsibly, clearly, and in a way that benefits both people and businesses.
This article shows some main ideas behind Data Ethics and Governance and simplifies some of the more complicated topics so they’re easy to understand.
In my long-form article we also looked at a real-world scandal, explore a data breach, and even look at some Python code that could help improve ethics and prevent leaks. I link that just down below for you guys!
As we wrap up this Data Analytics series, it’s important to dive into these two topics—because together, they help ensure data is handled in a responsible way. By the end of this article, you’ll see why being ethical is essential in data analytics and how good governance helps protect the integrity of the data and keeps trust intact.
This is all part of my current series on Data Analytics, which started with an introduction and has taken us through Exploratory Data Analytics and into Machine Learning. I created this series for you, my readers!
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Here is the long form article which included a famous ethics scandal, a major data breach, and code examples you can implement today to keep on top of ethics!
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What Is Data Ethics?
Data ethics is all about the moral guidelines that steer how we collect, analyze, and use data. As data analysts and scientists, we’re not just dealing with numbers—we have a responsibility to handle data in a way that’s ethical and respects people's privacy and rights.
The main question at the heart of data ethics is: Just because we can do something with data, should we? This is a key question that every data professional needs to think about when making decisions around data collection, analysis, or sharing.
There are other important questions to consider in today’s world:
Should we even be collecting this data?
Is it right to analyze this data in this way?
Could our findings hurt certain individuals or groups?
Data ethics highlights the importance of respecting privacy, avoiding harm, and ensuring fairness when working with data. In practice, this means being transparent, accountable, and fair in how we manage and use data.
Why is Data Ethics Important?
Think of data analytics like cooking a meal. If the ingredients (data) are bad or the chef (data analyst) doesn’t handle the cooking right (analysis), the final dish could make people sick.
In the same way, if data is used unethically, it can lead to harmful results—like biased algorithms, privacy violations, or unfair decisions.
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What is Data Governance?
While Data Ethics is about doing the right thing with data, Data Governance is like the rulebook for how data should be managed. It’s the system that makes sure data is available, secure, and used properly throughout its entire life cycle—from when it’s collected to when it’s deleted.
Basically, Data Governance is a set of guidelines that organizations follow to keep their data accurate, safe, and responsibly used. You can think of it like traffic laws for data: just like we need rules to keep roads safe, we need rules to ensure data is handled the right way.
Data Governance makes sure data is correct, consistent, and protected. It defines who gets access to data, how it’s stored, and what steps are in place to prevent unauthorized use.
By having good governance in place, companies can reduce the risk of data breaches and stay compliant with important regulations like GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act).
The Key Parts of Data Governance
Data Quality Management: Making sure data is accurate, complete, and up to date. Bad data can lead to bad analysis, which means bad decisions. Imagine making a financial investment based on old information—it’s like trying to navigate a ship with an outdated map.
Data Security: Keeping data safe from unauthorized access or breaches. This is especially important in fields like healthcare or banking, where personal info can be very sensitive. A data breach could lead to identity theft, financial loss, or even put people’s safety at risk. To protect data, companies use things like encryption, access controls, and regular security checks.
Data Stewardship: Giving specific people the responsibility of managing data. Data stewards make sure the rules for handling data are followed and that it’s used safely and correctly. They’re basically the caretakers of the data, making sure it’s treated properly.
Data Compliance: Making sure all data practices follow the law. This includes sticking to regulations like GDPR in Europe, which sets strict rules about how personal data is collected and used. If companies don’t follow these laws, they can face huge fines and damage to their reputation.
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Conclusion
Data ethics and governance aren’t just optional anymore—they’re critical. As we rely more on data, it’s vital that we treat it with respect, honesty, and care. Whether it’s getting proper consent or putting strong data management rules in place, these steps help make sure that data is used to benefit everyone, not cause harm.
At the core, ethical data practices remind us to put people first. This way, the work we do as data analysts can make a positive, lasting difference in the world. I hope you guys found value in this article, let me know in the comments here below!