We are in a digital age today, where everything we do is 100x easier compared to 20 years back. This is due to the digital landscape, where data plays a crucial role. Many people term data to be a radioactive substance rather than gold or oil. While data has extreme potential to change how we run things in the business world, there are also cons or risks if this data is mishandled.
And this is when, there is a need for responsible data management, especially when we have Artificial Intelligence (AI)
Back in the 2010s, the focus of organizations in different industries was to collect huge amounts of big data. By the time we reached the 2020s, the emphasis or the focus moved to collecting and managing high-quality data for specific requirements or purposes.
Now, with generative AI (Gen AI) taking over industries by storm, the definition of data now involves different types of content such as articles and videos, further adding complexity and risk.
Data is said to be a very powerful tool, but it can be used against you if it is not managed properly. Data governance is quite critical due to privacy regulations and GenAI. It is recommended that companies avoid collecting irrelevant data, should start managing environmental impacts, and ensure data security at all times. The reason behind this is that poor data quality may hamper AI models and could be a costly error for companies.
To make data work for them, companies should start improving their data collection and creation process, make sure that the data is high-quality, and align data governance with their business objectives.
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