With more data professionals using AI tools, let’s explore five different ways that you can incorporate this powerful technology into your data analytics workflow.
1. Code Generation and Error Debugging
Arguably one of the most useful applications for AI is in generating code and/or debugging errors that are causing issues. AI is already powerful enough to handle complex tasks, including constructing machine-learning models and visualising extensive datasets.
It is also possible to ask AI to provide comments on your code. This can help to save valuable time when documenting the purpose of the code you have created.
2. Synthetic Data Production
Current research suggests that by 2030, synthetic data will be used in the majority of the AI training process. Synthetic data is particularly useful for data scientists and machine engineers, as certain training datasets can be difficult to obtain, such as video content and images.
Automated data imputation can also have a range of benefits for businesses, as it can help to complete datasets that have missing information much faster and more accurately than any other method.
3. Extracting and Explaining Key Insights
AI has the ability to look at large quantities of data and clearly explain why certain events occurred. For example, your data analysis company could ask AI why your sales fell in a particular month or ask it to identify the source of a sudden increase in users.
This can be extremely useful when drawing insights from your data, which you can then use to make more informed business decisions that will help you achieve your objectives.
4. Reporting and Dashboard Creation
If you have worked with a data analysis company, you’ll know how valuable dashboard creation and reporting services are. AI can be used in myriad ways to generate accurate reports, which present complex data in ways that are easy to understand.
5. Entering Data from Images
Entering data from images has historically been a time-consuming task but AI can automate this process. This is particularly useful for businesses that handle large quantities of data from documents and images.
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