PH Deck

Businesses and professionals are overwhelmed by massive amounts of qualitative data, leading to time-consuming manual analysis. The drawbacks of the old situation include spending too much time manually crunching data and not being able to efficiently draw actionable insights.

Users rely on coding-heavy tools like Jupyter notebooks for data analysis, requiring coding skills and facing a time-consuming process to generate insights.

Users need technical skills like SQL/Python or rely on experts to analyze data, facing inefficiency and dependency due to manual processes.

Investors currently rely on traditional methods of stock analysis which can be time-intensive and may lack real-time data.

Traditional methods of stock analysis can be cumbersome and outdated.

Users manually extract web data or use basic tools, facing high time consumption, frequent errors, and unstructured data challenges that hinder decision-making.

Users face challenges in understanding how leading companies leverage data to drive impact

Users rely on non-professional opinions (e.g., partners) for makeup feedback, leading to repetitive requests and inconsistent guidance.

Users struggle to transform Excel files into data dashboards and analysis reports efficiently, spending extensive time on data analysis and report writing. The process is often manual, slow, and prone to errors, which hampers productivity and efficiency.

Users currently manipulate spreadsheet data using complex formulas or scripts, requiring technical skills like Excel formulas or scripting, which is time-consuming and inefficient for non-technical users.