One of the main data trends for 2024 is the democratization of data. There is potential to integrate these two elements and change how businesses perceive and access their data since artificial intelligence (AI) is being used by many firms and is growing dramatically in use. PBT Group’s Data Engineer, MJ Scholtz, examines it more closely.
Working with a variety of platforms, tools, and settings, I have direct experience with how businesses are turning their attention to artificial intelligence. Artificial intelligence (AI) has many advantages, including the ability to automate intricate data analysis processes. This facilitates the extraction of valuable insights from big datasets by non-technical people, improving end-user experience and supporting faster, more precise data-driven decision-making.
That being said, businesses need to exercise caution so as not to become too dependent on it to the point where it begins to stifle workers’ thought processes. According to Scholtz, we shouldn’t just hand over our cognitive processes and analytical skills to AI; instead, we should utilize it as a tool to improve them.
Naturally, AI plays a significant role in data democracy by enabling businesses to overcome several conventional obstacles. Consider it, for instance, as one of the best strategies for closing the company’s technical skills gap. The majority of AI technologies provide consumers access to a user-friendly platform that exposes them to company data. With the help of these technologies, employees may more easily search and find data inside the firm without requiring technical expertise to use databases or specialized integration tools.
“Opening up the reporting structure is another way AI is facilitating the transition to data democracy. Reports in companies are often organized hierarchically. These are heavily influenced by use cases and often lead to the Business Intelligence (BI) professional or director compiling the data into a report that they believe would be of interest to readers.
According to him, artificial intelligence (AI) offers a more comprehensive perspective on data by enabling users to investigate internal corporate resources and make informed choices across all organizational levels, all while promoting inclusivity.
A better setting for the analysis
Although it is now simpler to acquire this data, there is also a greater chance that sensitive information might be misused or compromised. It is essential to guarantee that initiatives aimed at democratizing data adhere to stringent security protocols and privacy laws.
AI has a lot to offer businesses in terms of meeting and managing data privacy and security policies. AI, for example, is capable of analyzing sensitive data without human involvement. This implies that the system may provide valuable results while analyzing and masking sensitive data without requiring human involvement. But AI can’t tell how trustworthy or dependable that information is.
Scholtz contends that artificial intelligence (AI) should be seen as a helpful tool that may provide consumers with insightful information about how to enhance data and spot any outliers that might not adhere to data standards.
He gives the example of address information.
“There may be an instance when an address field seems to be located in a foreign nation. People may be unaware of the format used by those nations’ postal or zip codes. Without requiring technical expertise or local knowledge from a person, AI may analyze it and provide recommendations based on the facts. Thus, AI offers a business a more trustworthy source of information than if they were to manually go through and analyze the data themselves,” he continues.
But Scholtz warns that despite AI’s tremendous growth and evolution rate as well as its speed, there are still questions about its accuracy and dependability.
It’s crucial to remember this while using AI tools: they can only analyze data that they have access to. As a result, there’s always a chance that certain AI algorithms could misunderstand the data or have biases, which might result in incorrect conclusions or judgments. Thus, before using an AI platform to make decisions, it’s critical to be aware of its limits.
The process of democratization may exacerbate preexisting prejudices in the absence of adequate supervision and ongoing observation, which might have serious consequences for the organization. It’s important to keep in mind that machines will never be able to think as creatively as humans. AI may not always be the best option in every situation, even though it could respond quickly to our requests. Where will humanity go if we cease being creative thinkers and turn to AI anytime we need help solving a problem?
In light of this, Scholtz advises businesses to adopt open AI procedures, provide people with sufficient training, and set up reliable governance structures to reduce these dangers.
In addition to giving end users a greater understanding of the data, a robust data governance system guarantees that the data is correct, consistent, and only available to authorized users. Furthermore, it provides some assurance that insights—whether or not they are aided by AI—can be relied upon, fostering an innovative and data-driven culture while protecting private data and adhering to legal requirements.
“Getting a better grasp of data in the organization and enabling individuals to contribute to insights and the accuracy of that data are the two main objectives of data democratization. In this procedure, artificial intelligence is quite important. But we have to be careful not to become too dependent on AI; instead, we should let technology support rather than take the place of our mental processes, says Scholtz.