Definition of a data ecosystem
A data ecosystem is literally defined as a complex network of data. A data ecosystem in reality is a platform that combines data from numerous providers and is designed to build value off of processed data.
Fortune Business Insights states "the global big data analytics market size was valued at USD 307.51 billion in 2023. The market is projected to grow from USD 348.21 billion in 2024 to USD 924.39 billion by 2032."
Big Data is an industry that relies on the consumer within the data ecosystem. Most consumers are currently passively entrenched in this ecosytem without their knowledge, and many Big Data companies being unable to clearly define this ecosystem on their websites implies that they benefit more from the data ecosystem when a user's involvement is passive. Major power is being handed to these data collection companies, and they'd like to keep it behind closed doors.
Ethical Concerns
Privacy and Security
Make very clear what data is being collected from the user. For example, Apple’s App Tracking Transparency requires users to opt-in before apps can start tracking data. Make privacy settings easy to find and understand. Spotify allows user to toggle what behavior is tracked by them. This makes the user more comfortable using the app.
Environmental Concerns
All data processed requires energy. Data ecosystems are resulting in the processing of massive data sets. Nature reports that the data ecosystem accounts for over 2% of all global emissions.
Wealth and Exclusivity
Amazon controls 32% of the global market share of the data collection industry. The price tag on their services often excludes smaller businesses having access to data. Democratzing data and having open cloud sources as opposed to "data vaults" can help lessen the negative impact the data ecosystem has.
Discrimination
Algorithms often reflect the biases in the data they are trained on, leading to discriminatory outcomes. Algorithms used by financial institutions may deny loans to certain demographics due to biased data, even when their credit is comparable to other groups. Human oversight is still necessary to prevent problems like this from occurring.
The Power of Data
Cambridge Analytica
Cambridge Analytica was able to collect data through Facebook quizzes and use it illegally. Cambridge Analytica obtained personal information from Facebook profiles without telling users; this information was then used to impact the 2016 U.S. presidential election.
Amazon Monopoly
Amazon has created a modern monopoly through big data. Amazon is the largest online retailer, and has millions of consumers with specifically designed algorithms with targeted ads and products. They are able to design these algorithms through predictive analysis made within the data ecosystem. Amazon is able to collect data itself through product purchases, but also through routes like Prime Streaming, or their in person grocery stores. Every interaction made by a user on Amazon.com proves profitable to them.
Building sustainable systems
An ecosystem should inherently benefit all individuals involved. To create truly sustainable data ecosystems, tech designers must balance cutting-edge industries with responsibility. This means prioritizing energy efficiency to reduce the environmental impact of data processing, democratizing access to data so that smaller businesses and underrepresented communities can participate, and embedding ethical principles into designing every stage of the data lifecycle. Designing systems that minimize harm and maximize inclusivity ensures that the data-ecosystem serves everyone.
https://www.dremio.com/wiki/data-ecosystem/#:~:text=Data%20Ecosystem%20refers%20to%20a,%2C%20manage%2C%20and%20consume%20data.
https://online.hbs.edu/blog/post/data-ecosystem
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https://www.cognizant.com/us/en/glossary/data-ecosystem
https://www.forbes.com/councils/forbestechcouncil/2023/10/27/data-ecosystems-how-information-sharing-improves-businesses/
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