Frank Fuzzy Marek’s Post

Data Analytics is the often complex process of examining big data to uncover information such as hidden patterns, correlations, market trends and customer preferences that can help organizations make informed business decisions. I am happy to share my new internship completion letter of Data Analytics.

Internship Project 9 Title: Costumer Shopping Analysis. Data Source: Quantum Analytic. Visualization Tool: Tableau Insight: ☑ Costumer by Gender. ☑ Quantity sold per Product Category. ☑ Payment method per Shopping mall. ☑ Average Price and Product Category per year trend. Attached is the full analysis clip.  Your review/feedback for this Analysis would be greatly appreciated My Heartfelt Gratitude Quantum Analytics NG Analytic NG Jonathan Osagie Christian Okwara. My Data Analytics knowledge from Quantum Analytics NG has been nothing short of an awesome experience, as the detail and simplicity in approach and methodology are superb, thanks to the GREAT TEAM.  #project #dataanalysis #datavisualization.

Hello, Here's my 10th project as an intern with Quantum Analytics NG! 🚀 Project 10: Customer shopping data 📊 Dataset: supplied by Quantum Analytics NG 🔧 Tool Used: PowerBi Based on the analysis, here are some recommendations for improving the performance of the stores: 1. since the majority of the customers are middle-aged, the stores should consider tailoring marketing efforts to meet the preferences and needs of customers within this age group 2. Since the majority of the customers are female, the stores can also target female customers in their marketing campaigns to appeal more to female customers. 3. Stores should consider optimising prices for clothing items to boost revenue. 4. The analysis revealed that some less popular products, like shoes and technology, generate more revenue, so the stores should increase their marketing efforts for shoes and technology and also review the pricing and profitability of these items to optimise revenue generation relative to product demand and profitability. 5. Stores should constantly monitor customer preferences and adapt to product supply, marketing strategies and pricing accordingly I'm grateful for the guidance of all the amazing facilitators for their support and valuable contributions throughout my journey towards becoming a data analyst, and to Jonathan Osagie and Quantum Analytics NG for providing the platform to learn and grow. I look forward to your thoughts and feedback on this project! 🙌 #DataAnalysis #InternshipJourney #PowerBi

I completed the first task of my internship at OasisInfobyte in the field of data analytics, where I gained practical experience in data cleaning and exploratory data analysis. I honed my skills in interpreting descriptive statistics and time series analysis and learned how to employ data visualization to effectively communicate insights. Project: Exploratory Data Analysis (EDA) on Retail Sales Data Description: In this project, I worked with a dataset that contained retail sales information. The objective was to conduct exploratory data analysis to discover patterns, trends, and insights that could aid the retail business in making data-driven decisions. Key Concepts and Challenges: Data Loading and Cleaning: I loaded the retail sales dataset and performed cleaning operations. Descriptive Statistics: I computed basic statistics such as mean, median, mode, and standard deviation. Time Series Analysis: I analyzed sales trends over time using time series methods. Customer and Product Analysis: I examined customer demographics and purchasing behaviors. Visualization: I illustrated insights using bar charts, line plots, and heatmaps. Recommendations: I offered actionable recommendations based on the analysis. Oasis Infobyte

As a Data Analyst Intern, it's a pleasure to share every step of my journey in the world of data analytics with you. Let's embark on this learning together as we delve into a beginner-friendly introduction to Data Analytics. #DataAnalytics#InternJourney"

"Elevate your organization's potential through the lens of data analytics. As an aspiring intern, I bring a passion for turning data into actionable insights, propelling your business into the future. Let's collaboratively unlock the untapped possibilities within your data, driving innovation, efficiency, and success. Together, we can shape a data-driven destiny for your organization."

Hello, Data enthusiast, here is one of my practical projects as an internship with Quantum Analytics. Visualization Tool: Excel/Pivot Table Data Source: Quantum Analytics The main objective of every Operational business is primarily focused on increasing revenue alongside customer satisfaction. However, in order to achieve this, different data are collected daily because these data are needed for stakeholders' decision-making. Businesses don’t just make decisions without proper data analysis. Business Objective: To explore the Dataset and create an interactive dashboard to explain key Performance Indicators (KPI) such as Total Revenue and total Quantity and identify Yearly Accrued Revenue for the years involved, to identify the product or item that yielded the highest Revenue, Region that generated the highest Revenue. Also, we want to know the salesperson who generated the highest Revenue in 2018 and 2019, the Top 10 Customers with the Highest Revenue, and the Customer with the Highest Quantity Purchase. I will be doing Exploratory Data Analysis (EDA) for this dataset with the aim of increasing revenue. It involves the initial analysis of the data to discover patterns and insights which typically include: Stage 1: Data Cleaning And Transformation Identifying and handling missing values, outliers, and errors in the dataset. Understanding the data was my first project. The Dataset has 17 Columns with about 2,000 rows. Few of the Columns are Order ID, Date, Customer ID, Customer Name, Sales Person, Region, etc The “Order ID” Column was pre-formatted as text instead of numbers. So, I had to clean it using the “CLEAN” function in a different Column. I created a different Column for “Year” and “Month” using the “TEXT” function. Moreso, because I needed to analyze sales by different quarters I created another Column for “Quarter” using a “TEXT” function nested with “OR” and “IF” functions. Thus: Quarter = IF(OR(TEXT([@Date], “mmm”)=”Jan”, TEXT([@Date], “mmm”)=”Feb”, TEXT([@Date], “mmm”)=”Mar”), “Q1”, IF(OR(TEXT([@Date], “mmm”)=”Apr”, TEXT([@Date], “mmm”)=”May”, TEXT([@Date], “mmm”)=”Jun”), “Q2”, IF(OR(TEXT([@Date], “mmm”)=”Jul”, TEXT([@Date], “mmm”)=”Aug”, TEXT([@Date], “mmm”)=”Sep”), “Q3”, IF(OR(TEXT([@Date], “mmm”)=”Oct”, TEXT([@Date], “mmm”)=”Nov”, TEXT([@Date], “mmm”)=”Dec”),”Q4")))) May I use this opportunity to thank Mr. Jonathan Osagie, Quantum Analytics NG, and the entire facilitators. Stage 2: Report, Visualization, and Dashboard The ETL process has to be completed as far as a data Analyst is concerned. Once the cleaning and transformation process is completed, the next step is to load the data for analysis. I created a Pivot Table and Calculated the Sum of Revenue, the Sum of Quantity, and the Sum of Total Revenue. I also created different tables such as Revenue by Sales Person, Revenue by item, Customer by Quantity Purchased, Revenue by Region, by Yearly Quarter, Revenue Over time, and Top 10 Customers by Revenue.

Internship Project 20 Title: Food App Business Report. Data Source: Quantum Analytic. Visualization Tool: Power Bi Insight: ☑ % No of Web Purchase and No of Store Purchase. ☑ Married, Single, Children and Teenage. ☑ % Of Campaign Accepted and Costumer Complian. ☑ Amount Spent on Wine, Fish, Gold, Friut and Sweet. ☑ No of Web Purchase and Store Purchase by Age. Attached is the full analysis clip.  Your review/feedback for this Analysis would be greatly appreciated. My Heartfelt gratitude to Quantum Analytics NG Jonathan Osagie Christian Okwara. My Data Analytics knowledge from Quantum Analytics NG has been nothing short of an awesome experience, as the detail and simplicity in approach and methodology are superb, thanks to the GREAT TEAM.  #project #dataanalysis #datavisualization.

I'm thrilled to share that I have completed task 1 of my Oasis Infobyte Data Analytics internship. I meticulously address missing values through strategic imputation or informed handling, while my keen eye eliminates duplicate records, guaranteeing data uniqueness and clear conclusions. Consistent formatting and units across datasets are my secret weapon for seamless analysis and accurate comparisons. I don't shy away from outliers; instead, I leverage my expertise to identify and handle them, ensuring my analysis reflects reality. This comprehensive approach transforms raw data into a polished foundation for uncovering valuable insights that drive impactful decision-making. It's not just a skill, it's a commitment to excellence in data analysis.

I'm thrilled to share that I've embarked on my data analysis journey with Quantum Analytics NG. As part of my internship program, I will be diving into various projects aimed at sharpening my skills in data analysis. I'm excited to navigate this journey and leverage my expertise to deliver impactful insights. I invite you to explore my first project and its an interactive Excel dashboard for Godswill Enterprise. Stay tuned for more updates as I continue to delve deeper into the world of data analysis. The data set contains sales information such as Date, Product, Unit Cost, Order Quantity, and Customer age. Project 1; Title: Interactive Excel Dashboard Visualization tool: Microsoft Excel Company: Godswill Enterprise Data Source: Quantum Analytics NG KPIs: =>Sum of Profit =>Sum of Revenue =>Sum of Total Cost =>Sum of order quantity Insights: =>Yearly trend of Profit =>Daily trend of Profit =>Age group impact on Profit =>Impact of gender on profit =>Impact of season on profit => Top 10 best-selling products Recommendation: Do more discounted sales for young adult in order to encourage them in buying more, more adverts should be put out to capture other age groups and incentives should be given. Kindly find the attached video and leave a comment of your honest suggestion or opinion Thanks to Quantum Analytics NG Jonathan Osagie Godswill Ojumeaka