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Open DataNet GPT—Data research assistant for Open Data Network
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Open DataNet GPT
Data research assistant for Open Data Network
Most popular alternative: DataSquirrel (988 saves)
GPT welcome message: Hi! How can I assist you with Open Data Network data today?
How can I analyze traffic data from the Open Data Network?
Show me patterns in healthcare expenditure data.
Create a report on the latest employment statistics.
Help me understand education data trends.
AuthorKenneth Bastian
Generated by ChatGPT
Open DataNet GPT is a powerful tool developed to aid in data research with the Open Data Network. This GPT is primarily designed with the capability to generate spreadsheets and analyze trends.
Following an intuitive approach, it simplifies the process of analyzing diverse datasets by creating clear and comprehensible spreadsheets. This feature curtails the time usually spent on data organization, thus making it a useful tool in areas requiring expedited data analysis.
Additionally, it can examine trends over a certain timeline, providing meaningful insights that might be instrumental in decision-making processes. This GPT exhibits impressive versatility as it can be utilized in a range of sectors including healthcare, traffic data analysis, employment statistics, and education.
In the spectrum of its functionality, the Open DataNet GPT is also able to guide users to understand education data trends and can conveniently create reports based on the latest employment statistics.
With the help of the Open DataNet GPT, an individual can be assisted in analyzing traffic data from the Open Data Network and discerning patterns in healthcare expenditure data.
Overall, this GPT is a comprehensive solution for researchers, analysts, and individuals or organizations interested in data from the Open Data Network.
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Releases
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November 3, 2023
Initial release of Open DataNet GPT.
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Prompts & Results
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Open DataNet GPT was manually vetted by our editorial team and was first featured on January 9th 2024.
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Reducing manual efforts in first-pass during code-review process helps speed up the "final check" before merging PRs -
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This team took the time to understand the industry, problem and its users and designed a perfectly engineered solution. Kudos.
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