ICI su LinkedIn: Addetto IT https://lnkd.in/dsmcVUCm Responsabile di… (2024)

Title: Road Accident Analysis Project Overview: The goal of this project is to create an interactive dashboard that visualizes road accident data.We’ll focus on accidents occurring in 2021 and 2022.Data Collection and Preparation: Raw data related to road accidents (e.g., accident location, date, severity, vehicle type) is collected.Data cleaning and transformation are performed using Power BI tools.Data Modeling and Relationships: A data model is created in Power BI, defining relationships between different tables (e.g., accidents, vehicles, victims).Key Visualizations:Maps: Display accident locations on a map.Bar Charts: Compare accident counts by month, day of the week, or time of day.Pie Charts: Show the distribution of accident severity (minor injuries, major injuries, fatalities).Line Charts: Track accident trends over time.KPIs and Metrics:Total Casualties: Calculate the overall impact of accidents.Accidents by Severity: Visualize the breakdown of accident severity.Vehicle Types: Analyze casualties based on different vehicle types.Time Intelligence Functions: Utilize Power BI’s built-in time intelligence functions for monthly trend analysis.Compare accident data across different time periods.Grouping and Aggregation: Group data by attributes like vehicle type, road type, and location.Understand casualties by road type and identify accident hotspots

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Project : ❌ Road Accident Analysis✅ Objective:Analyzed road accidents to provide valuable insights and mitigate incidents. Leveraged dummy data for a comprehensive study, focusing on different vehicles, surfaces, and weather conditions to enhance safety and support stakeholders.✅ Processes:Conducted thorough Data CleaningApplied Data Preprocessing techniquesUtilized Data Visualization for insightful presentationsPrimary KPIs:🔴 Total Casualties: Examined total casualties over two years🔴 Serious Casualties: Analyzed serious casualties for two years🔴 Slight Casualties: Investigated slight casualties over two years🔴 Casualties by Car: Explored casualties specifically involving cars over two years✅ Key Analytical Outputs:Presented total casualties by different vehicle typesConducted a year-over-year comparison to gauge the trend in accident numbersAnalyzed casualties based on different road types, surfaces, and areasExamined casualties in varying light conditionsDynamic Insights:The project's flexibility is demonstrated through the use of slicers for Accident Date and Locality Type (rural, urban), allowing real-time adjustments to the presented information.✅ Tools Used:ETL (Extract, Transform, Load) processesExcel for comprehensive data analysisPivot Tables for dynamic and interactive reportingThis project not only showcases technical skills in ETL and Excel but also highlights a commitment to road safety through data-driven decision-making.

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When using risk data to discover high-risk drivers, triangulation is a well-trodden path that uses multiple data sources to corroborate findings, validate interpretations, and enhance the overall credibility of the result.By looking at driver risk from different angles, Driversure can enhance the trustworthiness and validity of its findings. This is proven ultimately by reducing the frequency and cost of motor fleet claims.By gathering risk data from multiple sources, Driversure reduces the risk of bias and gains a more comprehensive understanding of the phenomenon of Fleet Risk that is being demonstrated.There is no good reason why fleets should keep diverse data sets in separate silos in separate departments and drawing conclusions based on an incomplete picture. Indeed, the knock-on effects are costly and wasteful.To consolidate risk data for all the good reasons above, email risk@driversure.uk or call 0113 224 8800 today.

Project Title: Road Accident Analysis Dashboard Excel📌 Portfolio Website: https://lnkd.in/gSJpFWqk📌 To view Dashboard: https://lnkd.in/g3K5Z3PeSummary:Problem Statement:To develop a comprehensive Road Accident Analysis Dashboard for the years 2021 and 2022, using Power BI, Tableau, and Excel. The dashboard aims to provide insights into total casualties, accident severity, casualties by vehicle type, monthly trends, road types, area/location, day/night incidents, and overall accident statistics.Dashboard Components:1. Primary KPIs: Total Casualties and Total Accidents- Metrics: Total Casualties, Total Accidents, Year-over-Year (YoY) Growth.- Software Used: Power BI, Tableau, Excel.- Insights: Provides a high-level overview of accident statistics and their growth over the years.2. Primary KPIs: Total Casualties by Accident Severity- Metrics: Casualties by Accident Severity, YoY Growth.- Software Used: Power BI, Tableau, Excel.- Insights: Analyzes the severity of accidents and trends over the years.3. Secondary KPIs: Casualties by Vehicle Type- Metrics: Casualties categorized by vehicle type for the current year.- Software Used: Power BI, Tableau, Excel.- Insights: Breakdown of casualties based on the types of vehicles involved.4. Monthly Trend Analysis- Metrics: Monthly comparison of casualties between the current year and the previous year.- Software Used: Power BI, Tableau.- Insights: Visualizes trends and patterns in accident data on a monthly basis.5. Casualties by Road Type- Metrics: Casualties categorized by road type for the current year.- Software Used: Power BI, Tableau.- Insights: Identifies patterns and risks associated with different road types.6. Casualties by Area/Location & Day/Night- Metrics: Casualties based on area/location and day/night incidents for the current year.- Software Used: Power BI, Tableau.- Insights: Examines accident patterns concerning location and time of day.7. Total Casualties and Total Accidents by Location- Metrics: Total Casualties and Accidents categorized by location.- Software Used: Power BI, Tableau.- Insights: Provides a detailed view of accident statistics based on different locations.Conclusion:The Road Accident Analysis Dashboard project successfully utilized Power BI, Tableau, and Excel to present critical insights into road accident data for the years 2021 and 2022. The SQL verification process ensures the accuracy and reliability of the presented information, providing a valuable tool for stakeholders to make informed decisions and implement safety measures.#roadaccidents #excel #dashboard #dataanalyst #dataanalytics

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Traffic Accident Analysis Dashboard Project Using SplunkIn my role as a data analyst, I developed the "Traffic Accident Analysis Dashboard" using Splunk to address the critical need for enhancing road safety through data-driven insights. This project involved a detailed analysis of traffic accidents across various counties and cities, focusing on identifying patterns, the impact of weather conditions on accident severity, and pedestrian accident rates in urban areas.The dashboard provides a comprehensive overview, showcasing accident counts in major areas like Los Angeles, Harris County, and San Diego among others. It includes visual representations such as bar graphs for county-level data, a pie chart for city-level distribution, and a line graph depicting the correlation between air pressure and accident severity. This visualization aids in understanding where accidents are more frequent and how external factors influence their severity, thereby assisting local government bodies in implementing targeted safety measures.Through this project, I utilized my expertise in Splunk for data ingestion, processing, and visualization. My ability to manipulate and analyze large datasets was crucial, as was my knowledge of creating interactive dashboards that present complex data in an easily understandable format. The skills I developed further include advanced data querying, real-time data analysis, and creating visually impactful reports tailored to stakeholder needs.The key insights from this project highlighted the need for improved traffic management and infrastructure enhancements in high-risk areas. Additionally, the analysis on the impact of weather conditions on accident severity prompted considerations for weather-adaptive traffic control systems.This project not only sharpened my technical skills with Splunk but also underscored the importance of data analytics in public safety initiatives. The dashboard serves as a vital tool for policymakers and traffic management organizations, aiding in the development of more informed and effective road safety strategies, ultimately aiming to reduce the incidence and severity of traffic accidents.Tools Used:SplunkSplunk EnterpriseSkills:Data ingestion and preprocessingAdvanced data queryingReal-time data analysisDashboard and visual report creationData visualization techniquesInterpretation and presentation of complex datasets

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Six Sigma is different from other quality initiatives because its main focus is to improve customer value and efficiency, and ultimately enhance bottom line of the organization (Pyzdek, 2003).Read more 👉 https://lttr.ai/APXsG#AccountingServices #GreaterEfficiency

Hello Connections,Excited to share my first power BI Dashboard on - the Accident Analytics Dashboard. I've just completed creating a dynamic dashboard in power BI and I can't wait to showcase the process behind it.Through this project, I gained valuable insights into the world of road safety. I learned the importance of thorough data cleaning to ensure accuracy and consistency. Processing the data allowed me to extract meaningful metrics and identify critical factors contributing to accidents. Utilizing statistical techniques and exploratory data analysis unveiled hidden patterns and trends. Here are some of its features:• Total Casualties Analysis• Casualties by Severity and Vehicle Type• Monthly Trend Analysis• Road Type Analysis• Casualties Distribution by Road Surface• Casualties Relation by Area/Location & Day/Night.Here's a quick breakdown of the steps I followed:✔DATA CLEANING: I removed inconsistencies, errors, and duplicates. This ensured that the information I worked with was accurate and reliable.✔ DATA PROCESSING: This involved organizing, sorting, and filtering the data to extract meaningful insights.✔DATA ANALYSIS: I used various statistical methods and exploratory techniques to gain valuable insights into the dataset.✔DATA VISUALIZATION: To make the analysis more accessible and visually appealing, I utilized powerful visualization tools. I created compelling charts, graphs, and interactive visuals to present the data in an easily understandable format.DASHBOARD: Finally, I integrated all the components into an intuitive and user-friendly dashboard.The total number of casualties that occurred after accidents is a staggering 417,883.Car accidents accounted for the highest number of casualties, contributing to 79.8% of the total. On the other hand, casualties were minimal in accidents involving other vehicle types. In the years 2021 and 2022, the total casualties were 222,146 and 195,737, respectively. Analyzing the trends between these two years provides valuable insights for targeted interventions.The analysis revealed specific months with the highest and lowest casualties, enabling focused strategies for different times of the year.By identifying the road types and surfaces associated with the maximum casualties, authorities can prioritize safety measures and road maintenance efforts accordingly. This Road Accident Analytics Dashboard opens the door to data-driven.decision-making, enabling stakeholders to implement evidence-based interventions that enhance road safety. It serves as a valuable tool for policymakers, traffic authorities, and safety advocates alike.Dashboard: Accident Analysis Dashboard!Data Visualization Tool: power BI

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In this segment we unpack customer due diligence (CDD)#Compliance

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Data integrity related to truck and trailer maintenance can directly impact cost efficiency, operational safety, customer satisfaction, and more. Read this blog to learn how to maintain your trucking operation’s data integrity.

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Data integrity related to truck and trailer maintenance can directly impact cost efficiency, operational safety, customer satisfaction, and more. Read this blog to learn how to maintain your trucking operation’s data integrity.