What's the data analytics program like at a $5B CU? In our newest "Day in the Life of A Data Analyst," learn how?$4.9B?Nusenda Credit Union?runs their data analytics department. We chat with?Stephen Bradley, a Data Integrations Manager who has been instrumental in helping the organization evolve into an industry pioneer in data-driven culture. "When I started at Nusenda, one of the goals was to get us off our outdated data system and onto something that’s built around modern technology," says Stephen. "We wanted to grow the department and make sure that we had all the right roles. We did the life support for the systems and processes, making sure the customers got what they expected every morning in their inboxes. We spoon fed different data needs to different areas directly from Excel. Now some of that was automated through SQL database mail, but there was manual overhead from my department to try and make sure that everything happened consistently as expected every day." Read about Stephen's organic journey into data analytics, as well as the challenges and successes of managing data analytics at a 20-branch credit union. #datananalytics #creditunion https://lnkd.in/dkUbEXqA
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"Before Alation, I would describe things as disjointed." — Elizabeth Friend, Senior Director of Data Governance at Sallie Mae. Prior to implementing Alation, the market leader for private student lending, Sallie Mae, faced problems like: ?? Distributed data ?? No formal data governance program How did they fix it? Find out: https://lnkd.in/eNmRdfyz #alationcustomers #salliemae #datasilos
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Data Analyst ?? | SQL | Advance Excel | Power BI | Python ?? | NoSQL (MongoDB) | Machine Learning ?? | Google Analytics | ETL
?? Hey ! LinkedIn family, I am Excited to share my latest project : "Credit Card Transaction & Customer Analysis" ?? Project Objective: Developed a comprehensive credit card weekly dashboard to provide real-time insights into key performance metrics and trends, empowering stakeholders to effectively monitor and analyze credit card operations. ?? Process: Prepared CSV files and created tables in MySQL. Imported CSV data into tables for ad hoc analysis. Connected the database to Power BI to streamline data processing and analysis. Used DAX queries to create necessary measures and added custom columns to the data. Developed a detailed dashboard to visualize insights. Shared actionable insights with stakeholders to support decision-making processes. ?? Insights (53rd Week) : ?? WoW Change: 1. Revenue increased by 28.8%. 2. Total Transaction Amount increased by 2.22% compared to the previous week. 3. Customer count increased by 1.80% compared to the previous week. ?? Overview YTD: 1. Overall revenue: $57M 2. Total interest: $8M 3. Total transaction amount: $45.5M 4. Revenue contribution: Male customers - $31M, Female customers - $26M 5. Blue & Silver credit cards contribute to 93% of overall transactions. 6. Top contributing states: TX, NY, CA - 68% 7. Overall activation rate: 57.5% 8. Overall delinquent rate: 6.06% This project was a great opportunity to leverage MySQL and Power BI to deliver impactful data-driven insights. GitHub Link : https://lnkd.in/gdftEABG Guided By : Rishabh Mishra #DataAnalytics #PowerBI #MySQL #CreditCardOperations #DataDrivenInsights #StakeholderEngagement Feel free to connect and reach out for any collaborations or discussions on data analytics and business intelligence!
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The life of Data analyst : 2 To save your time in analysis, the first step should be understanding the business definition instead of directly jumping into writing script for given transformation logic. understand the drama behind that transformation, why they want to do it. if you are into the banking domain, you may relate the scenario. The loans department requires their unique id to be in form of 'Loannumber|customer_account_number' while for saving or current account demands it should be only in form of 'cust_account_number' but business definition will tell you everything. in this scenario it may be like this - unique identifier of customer who may or may not opt for loan. which is clearly indicating that if the unique id contains '|' , it will belong to some loan. that's it. pro tip: talk to a business person first before you start typing your code. happy learning!! #datanalyst #dataengineering #etl
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Postgraduate in Mathematics | Proficient in Business & Data Analytics | SQL, Excel, Tableau, Power BI, Python, Statistics | Data Insights & Decision-Making
?? Excited to Share My Latest SQL Project: Loan Analysis ?? I’ve recently completed a comprehensive Loan Analysis Project using SQL, and I’m thrilled to share the insights I’ve gained from this work! ?? Project Overview: In this project, I analyzed a loan dataset to derive key insights for strategic decision-making in the banking sector. The analysis focused on: Loan Approval Rates: Analyzing the loan approval percentages based on factors like homeownership and loan intent. Debt-to-Income (DTI) Ratios: Calculating and categorizing DTI ratios to identify risk levels in loan applications. Default Percentages: Identifying and calculating default percentages based on various loan attributes. ?? Key Findings: Categorized DTIs into Good, Average, and Risky bands to determine potential risks. Leveraged SQL to uncover trends that can guide loan approval strategies. Generated actionable insights that can help in reducing default rates and improving loan strategies. ?? Skills Used: SQL Queries: Complex aggregations, joins, and subqueries. Data Analysis: Identifying key performance indicators (KPIs) and making data-driven decisions. Reporting: Presenting insights for better decision-making in the banking and finance sectors. This project not only strengthened my SQL skills but also gave me a deeper understanding of the financial sector and how data can drive impactful decisions. ?? Looking forward to diving into more complex data-driven projects and continuing to grow as a data analyst! A big thanks to Samraat Pattanayak #DataAnalysis #SQL #Finance #LoanAnalysis #Banking #DataScience #ProjectShowcase #DataDriven #BusinessIntelligence #Analytics
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Credit cards offer the convenience of cashless payments and the ability to build credit history. They work by allowing users to borrow funds up to a predetermined limit for purchases, which must be repaid by the due date to avoid interest charges. I'm thrilled to present my recent work on analyzing credit card transaction data using SQL and visualizing the insights with Power BI. This project aimed to uncover spending patterns, detect trends, and provide comprehensive reports on credit card usage. ?? Key Insights: Overall Revenue: $55M Total Interest Earned: $7.84M Total Income: $588M Customer Spend Score (CSS): 3.19 Revenue by Gender: Male - $30M, Female - $25M Top Contributing States: TX, NY, CA Card Category Performance: Blue and Silver cards contribute 93% of transactions Activation Rate: 57.5% Delinquency Rate: 6.06% ?? Technologies Used: SQL, Power BI This project has given me invaluable experience in data analysis and visualization, and I'm excited to apply these skills to new challenges. Feel free to check out the full project on my GitHub repository, the link in?comment #DataAnalysis #SQL #PowerBI #DataVisualization #CreditCardAnalysis #DataScience #BusinessIntelligence #Geekster Ragini Mishra Krishna Madan Geekster Guided by : Kunal Gaur
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Aspiring Data Analyst | Passionate About Turning Data into Business Solutions | Excel, Power BI, SQL, Python |
Hey everyone, how are you managing to stay so incredibly average in this world of extraordinary people? Just curious! ?? I have completed my weekly #credit_card analysis project using #MySQL and #Power_BI. I would appreciate any feedback or suggestions you might have. Additionally, if you have any dataset or topic recommendations for my next project, please feel free to share. Project Objective: To develop a comprehensive credit card weekly dashboard that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively. (USA Data) Project Insights: Week-on-week changes: -Revenue Increased by 28.8% -Total Transaction amount increased by 35% and transaction count increased by 28% -Customer percentage increased by 12%. ? ? Overview Year to Date: -Overall revenue: 57 million -Total interest is 8 million -Total transaction amount is 46 million -Male customers are contributing more in revenue 31 million and females 26 million -The percentage of males is 58% and females 42% -Blue & Silver credit cards contribute to 93% of overall transactions -TX, NY & CA are the most contributing states with 68% overall -Overall Activation rate is 57.5% -The overall delinquent rate is 6.06% -Most delinquents are self-employed. Github: https://lnkd.in/g4ccsQh2
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South Shore Regional Centre for Education || Business Intelligence Expert || Business Strategy
Few days ago while having a quick chat with an acquaintance I mentioned that I was a Data Analyst, and he got completely locked in to the conversation because he was looking to switch career paths. He asked me to teach him how to clean data in Excel. Of course, his request was granted and I made this video tutorial. Thought to share it here so someone else could learn a thing or two. Having worked in Finance as a Data Analyst, my example leveraged a retail bank scenario #dataanalyst#datacleanup#businessanalyst#msexcel#tutorial#experienceddatanalyst#datamodeller#vba#finance#tech#financetech#financegirl#techgirl#excel#exceltutorial
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Data Analyst Intern | Skilled in Python, MySQL, ML, Power BI, Excel | Google and Microsoft Certified
?? Excited to share my latest project where I combined my SQL and Power BI skills to create a dynamic and insightful dashboard for credit card operations! ?? ?????????????? ????????????????????: ???? ?????????????????????? ????????: ? Detailed analysis of transactions and revenue. ? Breakdown of transaction volume by job, education level, and quarter. ???? ???????????????? ????????: ? Comprehensive customer insights with gender comparisons. ? Age group expenditure and revenue trends. ? Top 5 states contributing the most revenue. ?????? ????????????????: ? Total Revenue: $57M ? Top Revenue States: TX, NY, CA ? Revenue by Gender: Male - $31M, Female - $26M ? High Performing Cards: Blue and Silver cards account for 93% of transactions. ? Weekly and Year-to-Date Trends: Wow! Significant increases in revenue and customer engagement. This project underscores the power of real-time data visualization and analysis in driving business decisions. #SQL #PowerBI #DataAnalytics #Dashboard #DataVisualization #BusinessIntelligence
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Data Collection When I first considered looking for a side income, I dreamed of becoming a Data Analyst. I didn’t realize that Data Analysts have to do a lot of tasks before providing a summary or analysis report. What surprised me the most was that Data Analysts need to do coding, which is an activity that always stresses me out! Now, as a Unit Trust and PRS consultant, I get to experience being a Data Analyst occasionally. Haha! To perform due diligence, determine which funds are performing well, and which ones to avoid, I have to analyze everything myself. So, the first step to take is data collection. Yesterday, I managed to do Data Cleaning and Matching. I only filtered for Shariah-compliant funds because those are the ones I will recommend to my clients. There’s a shortcut to finding out which funds perform well—just ask a Financial Planner ??. Or, we can attend a webinar organized by my FP to gain knowledge together.
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??? Throwback to My First Project as a Data Analyst! I’ll never forget this memorable project—it was equal parts funny and fulfilling! My first client approached me with a simple request: create a dashboard to analyze her bank’s financial health. Her budget was tight, and her expectations were modest. Her exact words? “Just something basic will do.” Fast forward a few days later, I presented the completed dashboard to her. As soon as she saw it, her jaw dropped, and her reaction was priceless: "You're an Excel wizard!" ??? She kept coming back for more projects, and that experience taught me an invaluable lesson: Excellence doesn’t depend on the reward—it depends on your attitude toward delivering quality. My guiding principle: "My goal is to produce quality, impactful work—regardless of the size of the reward." Over the years, I’ve come to understand a simple truth: Wealth is not in money but in people. After all, money derives its value from the people who create it. So when I work for a client, their satisfaction is my top priority. ?? A quick overview of this dashboard: This comprehensive financial health dashboard for a leading bank does more than just crunch numbers—it provides actionable insights at a glance. Here’s what it offers: ?? Profitability Metrics: Comparing Return on Assets (ROA), Equity (ROE), and Net Margin across competitors. ?? Revenue & Net Income Trends: Track year-over-year changes and highlight growth opportunities. ?? Capital Adequacy Ratios: Measure the bank's financial stability with Tier 1 and Total Capital insights. ?? Efficiency & Employee Trends: Correlating employee count with productivity. ?? Long-term Projections: A 5-year forecast to assist in strategic planning. I designed it to be visually compelling, intuitive, and actionable, even for a non-technical audience. Seeing my client “wowed” reminded me why I love what I do: empowering decision-making through data. ?? Takeaway: Always put in your best effort—whether or not people expect it. Excellence will always speak for itself! ? ? And remember: true wealth lies in the relationships and people you build along the way. ?The antidote to competition is indispensable value. And also, you don’t need many clients, you only need a few who truly value your work and recognize the indispensable quality you bring to the table. Have you ever delivered something that exceeded expectations? Share your story below—I’d love to hear it! Chisom Ibemere #DataAnalytics #ExcelDashboard #ClientSatisfaction #WealthInPeople #QualityOverReward #BankingInsights #FinancialAnalysis #Throwback
Experienced problem solver, bridging technology and business processes
1 个月Thanks Gemineye and Brewster Knowlton for your great partnership on our data journey here at Nusenda Credit Union. And that's for this opportunity to share a bit about my professional journey.