Psyliq

Hello everyone! ✨ Insights from my project, Ben Pizza In this project, our primary focus was on creating a custom-built relational database tailored specifically for Ben's pizza shop. Our aim was to streamline order management and inventory tracking, similar to leading chains like Domino's. By leveraging interactive dashboards, we've empowered Ben to monitor key business metrics in real-time, enabling him to make informed decisions and drive growth. Project Highlights: 🔹 Data Normalization with QuickDBD: We used QuickDBD to define a clear data structure from the start, ensuring efficient data organization. 🔹 SQL Queries and Dynamic Dashboards: SQL queries were utilized to extract and refine data, resulting in three dynamic dashboards for Orders, Inventories, and Staff. These dashboards provide comprehensive insights into order trends, inventory levels, and staff performance. Project Overview: Situation: Ben is launching a new pizzeria, focusing on take-out and delivery. He needed a bespoke relational database to capture crucial data on orders, inventory, and staff, enabling him to track business metrics and create dynamic dashboards for insightful analytics. Task: The initial phase involved creating an orders table with fields for item details (name, category, size, price, quantity) and customer information (name, delivery address). The project also included data normalization, incorporating associated tables, and establishing table relationships. Action: We crafted distinct tables to manage various aspects like customers, orders, addresses, items, recipes, ingredients, inventory, rota, shifts, and staff. Each table was assigned a unique ID for interconnection. The database was then prepared for utilization in MySQL, and a dashboard was developed to oversee and assess the pizzeria's performance. Result: Upon project completion, Ben will have a robust database capable of seamlessly managing customer orders, streamlining stock management, and enhancing staff oversight. Interactive dashboards derived from this database will allow Ben to monitor and assess his business's performance, empowering informed decision-making with real-time data insights. Thanks for supporting my previous projects. I look forward to your continued support! 😊 WsCube Tech SkillUp Online Mentorness Psyliq Big Data & Analytics Lab Canada Inc. Xeven Solutions ArhamSoft (Pvt) Ltd sevenSolutions BrainX Technologies Nextbridge Ltd. Dubizzle Labs IVT Technologies PureLogics StackUp Contour Software Systems Limited Intellicode DELSOL InvoZone VentureDive ZAPTA Technologies (Pvt.) Limited Devsinc DevBatch DevBunch Private Limited #dataanalyst #datavisualization #sql #tableau #excel #python #powerbi

Hello Everyone! I am absolutely thrilled to share that I have completed the 3rd and final task at Psyliq! In this project, I aim to analyze and gain insights from a comprehensive dataset encompassing various aspects of employee demographics, job roles, satisfaction levels, and performance metrics. By leveraging tools like Power BI and Excel, I uncovered patterns, trends, and correlations within the data to inform strategic decision-making and optimize organizational effectiveness. From examining factors influencing employee attrition to understanding the impact of salary adjustments on income, my analysis endeavors to provide actionable insights that drive workforce management, improve employee satisfaction, and enhance overall business performance. Through thorough examination of the dataset and application of advanced analytical techniques, I seek to deliver valuable insights that empower stakeholders to make informed decisions and foster a thriving work environment. #HRanalytics #PowerBI #Excel #Psyliq #Internship #Accomplishments #LearningandGrowing

Excited to share about my project on Employee Data Analysis using Excel during my internship at Psyliq The project aims to analyze employee data to gain insights into various aspects of workforce management and performance. Utilizing tools like pivot tables, conditional formatting, and visualizations, to summarize and interpret key metrics. Takeaways: 1. Summarize Data:   - Create pivot tables to summarize employee counts by department and average engagement scores.   - Build multi-level pivot tables to analyze performance scores by business units and job functions. 2. Data Visualization:   - Create charts to visualize work-life balance scores and the relationship between training duration and cost.   - Design a dynamic chart for visualizing employee performance over time. 3. Conditional Formatting and Filtering:   - Apply conditional formatting to highlight low performance scores.   - Filter data to display only terminated employees and identify common termination types. 4. Data Calculation and Lookup:   - Calculate average satisfaction scores by gender.   - Use VLOOKUP to find supervisor email addresses and INDEX and MATCH functions for training program names. 5. Advanced Analysis:   - Create histograms for exit date distribution.   - Use SUMPRODUCT for calculating total training costs by location. 6. Automation and Optimization:   - Build macros to automate updating and refreshing pivot tables.   - Implement advanced conditional formatting for top and bottom employee ratings.

I'm thrilled🚀 to share📢 my recent project where I analyzed 📊 data from Paytm Mall's ePurchase. This was part of an assessment provided by Psyliq , and it gave me the opportunity to sharpen my data analysis skills. Here’s an overview of the project and my findings: Project Highlights🔲: Category Analysis: Identified the top 5 shipping cities in terms of the number of orders and provided a detailed analysis of products in the "Electronics" category. Data Filtering and Sorting: Filtered the data by Sale_Flag and sorted by Item_Price to identify the most expensive item. Conditional Formatting: Highlighted products with a Special_Price_effective value below $50. Sales Insights: Created pivot tables and visualizations to assess total sales value for each category, and calculated the average quantity sold in the "Clothing" category grouped by "Product_Gender." Revenue Analysis: Found the top 5 products with the highest Value_CM1 and Value_CM2 ratios and calculated the total revenue generated from Electronics category products with a Sale_Flag of 'Yes'. Category and Class Trends: Identified the top 3 "Class" categories with the highest total sales and calculated the total sales for each "Brand". Geographical Insights: Found the top 5 shipping cities based on average order value and determined total orders and total sales amount for each "Product_Gender" in the Clothing category. Category Contributions: Calculated percentage contributions of each category to overall total sales and identified the category with the highest average Item_Price. Revenue Trends: Identified the month with the highest total sales revenue. Conclusion: Skills ✍️Applied: Data cleaning, analysis, and visualization using Excel and Python (converted Excel file to CSV for easier access). Key Learning: Hands-on experience with data analysis challenges, particularly when dealing with missing date columns. Learned to find creative solutions such as working with CSV files. Experience 💻 with Psyliq : This assessment provided an excellent opportunity to deepen my understanding of data analytics and showcase my ability to derive actionable insights from complex datasets✅. I want to extend my gratitude 🙏 to Psyliq for this opportunity. It has been an invaluable experience that has helped me grow as a data analyst. If you have any questions or want to collaborate🤝, feel free to reach out! This is my work so go through this 👇