Claude 3.5 Sonnet: Anthropic’s Latest AI Enables Data Analysis

Anthropic, a leading AI company recently backed by Amazon with a significant $4 billion investment, introduced its latest model, Claude 3.5 Sonnet. This update now includes a data analysis tool, bringing some intriguing capabilities to users, though its execution holds some limitations. This article delves into Claude’s data analysis features, comparing it with ChatGPT’s offerings, and highlighting its practical usage and limitations.

Generating Code for Data Analysis

Both Claude and its main rival, ChatGPT, utilize code generation for data analysis. This means users can send prompts, and the AI will write the necessary scripts to parse and process data.

Claude generates code in JavaScript, while ChatGPT uses Python. This difference can be significant, especially since Python has a rich ecosystem for numerical analysis, machine learning, and big data. On the other hand, JavaScript is strong in web-based data visualization.

Claude’s Data Analysis Capabilities

• Code Generation: Claude writes code in JavaScript to handle data processing tasks.
• Upload Limits: There are strict limits on the data you can upload. For the free version, users are limited to a combined 30MB file size.
• Message Limits: Additionally, there’s a limit to the number of messages you can send within a sessions, requiring more frequent conversations to process large datasets.

To test Claude’s capabilities, I downloaded a dataset from data.gov. This dataset contained baby name information across nearly 145 years. However, when trying to combine multiple files for analysis, I encountered challenges due to its strict size limits, further constraining data handling.

Claude’s Visualization

Claude also includes a visual data representation feature, allowing users to generate charts and tables. However, my experience revealed some limitations, such as irregular data labels in charts. This limitation was particularly noticeable with JavaScript-based pie charts.

Practical Usage

For practical usage, I combined several datasets from data.gov. I tested Claude with different data sets, including smaller-size and single-year data files. Each case demonstrated the limitations of its data ingestion capacity.

For example, I started by trying to analyze 145 CSV files. To overcome the file-size limitations, I consolidated the data files logically by decade. Despite these efforts, I was faced with significant limitations in file size and message volume.

Comparing Claude to ChatGPT Plus

ChatGPT‘s Advanced Data Analysis feature is more robust, offering significantly higher data processing capabilities. Tested performance-wise, I sent several substantial datasets to ChatGPT Plus, all of which handled efficiently.

• Capacity: ChatGPT Plus can handle considerably larger datasets and longer session interactions, making it a better choice for detailed data analysis.
• Output Quality: ChatGPT Plus consistently produced clean, well-labeled charts, unlike Claude’s occasional visual quirks.

Conclusion

Overall, while Claude 3.5 Sonnet marks an innovative step forward in data analysis through AI, the tool faces critical limitations in its free version. More extensive data processing, seamless visualization, and prolonged session capabilities are more a reality with ChatGPT Plus.

Is Claude Right for You?

If you’re looking for detailed, accurate, and impactful data analysis capabilities, ChatGPT Plus remains the more effective choice. Nevertheless, Claude’s integration of JavaScript’s visualization tools makes it a creative alternative for web-based charting. However, given Claude’s free and Pro limitations, expect significant hurdles for large-scale data processing tasks.

If you’re considering employing these tools, you should be aware of their differences. Free users should evaluate whether Claude’s design fits their needs, while professionals handling large datasets may find the Pro or Plus subscriptions more cost-effective.

Call-to-Action

Would you like to use Claude or ChatGPT for your data analysis needs? Share your thoughts and experiences in the comments below. Let’s discuss which tool is best suited for your use cases!