Asha Holla
Analytics Engineer @ Bloom Value | AI, Automation, BI | Data Nerd
Bengaluru, India
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Asha is an Analytics Engineer at Bloom Value, working in the US healthcare space with over 2 years of experience in the Azure data ecosystem. She’s passionate about integrating AI and LLMs into everyday workflows to make work faster, smarter and sometimes just more fun.
She enjoys building solutions that automate “10-minute tasks” (even if it takes her 10 hours to perfect them). When shes not geeking out over data, Asha is a technical blogger, content creator, and speaker who belives knowldege multiplies when shared. She’s also an advocate for inclusive tech communities and an active ally supporting women in tech
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Boosting Data Processing: Performance Tune Pandas
This talk will be a in-depth exploration of techniques to enhance the performance of Pandas, the powerful data analysis library in Python. It will cover strategies, tips, and best practices for optimizing data processing workflows, leading to faster and more efficient analysis.
Recognizing the challenges posed by big data, we're well aware that Pandas can struggle with large datasets. Given that optimization is integral to tech, this talk delves into effective strategies for accelerating Pandas operations be it simple transformations on data or data export/imports to databases. I will also cover alternate supporting libraries to use and simple modifications to existing code to speed up execution.
We will have a live demo with code snippets demonstrating the usage and performance comparison as opposed to traditional methods which are used widespread.
This session aims to address 4 key points:
Why pandas is slow when it comes to handling big data?
Slight code modifications to existing pandas code syntax
Using different libraries to speed up execution - like SQLAlchemy, NVIDIA’s RAPIDS cuDF library among others
Performance comparison between proposed and existing methods
Drawing from personal experience, I'll share tried-and-tested methods to optimize Python scripts using Pandas and reduce pipeline execution time, ultimately enhancing resource efficiency.
Supercharge data analysis: Integrating Python in PowerBI and Excel
Power BI and Excel are two of the most widely used tools for data analysis and visualization. However, integrating Python into these platforms can significantly enhance their capabilities, enabling more sophisticated data manipulation, advanced analytics, and custom visualizations.
In this talk we will explore the powerful combination Python and these data tools. This session is designed for data analysts, business intelligence professionals, and anyone interested in unlocking the full potential of their data.
Key Topics Covered:
1. Introduction to Python Integration: Overview of how Python can be integrated into Power BI and Excel and its benefits
2. Advanced data Manipulation and Transformation: using libraries like Polars and Pandas
3. Integration of machine learning algorithms into PowerBI/Excel
4. Custom Visualizations: using open source python libraries like Matplotlib, Plotly, etc
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