{"id":3872,"date":"2024-06-26T07:00:12","date_gmt":"2024-06-26T07:00:12","guid":{"rendered":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/?p=3872"},"modified":"2025-11-11T12:16:00","modified_gmt":"2025-11-11T12:16:00","slug":"global-automotive-supplier-modernizes-reporting-iot-insights","status":"publish","type":"post","link":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/case-studies\/global-automotive-supplier-modernizes-reporting-iot-insights\/","title":{"rendered":"Global Automotive Supplier Modernizes Reporting for IoT Insights"},"content":{"rendered":"

A global automotive supplier recognized the critical need to enhance customer experience and operational efficiency within its micromobility business unit. This initiative called for an innovative reporting approach capable of handling extensive data from diverse sources, including IoT battery data and customer experience metrics from mobile applications.<\/span>\u00a0<\/span><\/p>\n

With challenges with disparate data sources and a need for actionable insights, they partnered with Wavicle\u2019s data, analytics, and visualization experts to\u00a0<\/span>modernize their reporting infrastructure<\/span><\/a>\u00a0using Amazon QuickSight. This empowered decision-makers to identify trends, track performance, and make data-driven decisions to enhance the overall performance of their battery supply.<\/span><\/p>\n

Outdated reporting and obsolete dashboards<\/span>\u00a0<\/span><\/h2>\n

In a strategic move to expand its operations into the micromobility market, this global automotive supplier established a partnership with a leading company based in Asia to provide batteries for their network of charging stations. This collaboration was a significant step forward for the supplier, marking its entry into the rapidly growing electric mobility sector.<\/span><\/p>\n

However, the expansion also brought the challenge of managing and using large amounts of data from IoT sensors tracking battery performance and mobile apps capturing customer experience data. Combining data from both charging stations and bikes made data management even more complex.\u00a0<\/span>\u00a0<\/span><\/p>\n

The company\u2019s existing Metabase reporting platform couldn\u2019t handle the high volume of incoming data, and they struggled with data modeling and scalability. Their outdated dashboards couldn\u2019t generate the reports needed to assess battery quality and make smart decisions to improve customer experience and overall business performance.<\/span>\u00a0<\/span><\/p>\n

To tackle these obstacles and harness their data effectively, the automotive supplier turned to Wavicle\u2019s data and analytics experts. To start the IoT analytics project, they sought to implement\u00a0<\/span>Amazon QuickSight<\/span><\/a>\u00a0and build out a set of 15 customized, user-friendly dashboards that offer insights into battery health,\u00a0battery and\u00a0charging station utilization, and energy consumption.\u00a0<\/span>\u00a0<\/span><\/p>\n

With this visibility, the automotive supplier would be able to make smarter decisions about battery maintenance, asset utilization, and energy consumption. Enabling this type of proactive battery maintenance and replacement was intended to decrease potential battery problems for customers and improve their overall experiences.<\/span><\/p>\n

Modernizing analytics infrastructure\u00a0<\/span>\u00a0<\/span><\/h2>\n

Wavicle\u2019s consultants collaborated closely with the automotive supplier\u2019s business teams to identify their reporting challenges and understand their data landscape thoroughly.<\/span>\u00a0<\/span><\/p>\n

After gathering a full picture of their business requirements, Wavicle implemented a new reporting platform to enhance data visualization and reporting capabilities. A new data reporting architecture was meticulously designed, and initial dashboards focused on providing insights into cost management, strategic maintenance, operational efficiency, and user experience.<\/span>\u00a0<\/span><\/p>\n

Wavicle\u2019s data engineers integrated IoT and mobile application data using leading technologies like Amazon S3 for scalable data storage, Apache Hudi for dynamic data processing, PySpark for building robust data pipelines, and AWS EMR with Apache Airflow for streamlined orchestration. The data was then organized into multiple layers \u2013 raw, processed, and analytics-ready data \u2013 ensuring its readiness for consumption by Amazon QuickSight dashboards.\u00a0<\/span>\u00a0<\/span><\/p>\n

This scalable, flexible, and efficient solution facilitated effective management of diverse data sources and delivered timely analytics to drive informed decision-making. The modernized reporting system provided detailed dashboards displaying crucial KPIs, empowering teams to improve both operations and outcomes.<\/span><\/p>\n

Clear reports and interactive dashboards improve operations\u00a0<\/span>\u00a0<\/span><\/h2>\n

Wavicle\u2019s team designed dashboards that demonstrate in-depth data analytics and the value of clear reporting for improving user experience and battery maintenance. These dashboards empower the company to identify trends and potential issues early to make proactive maintenance decisions and raise the quality of battery health in their micromobility fleet.<\/span>\u00a0<\/span><\/p>\n

The implementation of a new reporting system using Amazon QuickSight facilitated rapid visibility into critical metrics such as battery health, battery and charging station utilization, and energy consumption. The revamped dashboard platform, comprising 15 tailored and intuitive dashboards, provided a comprehensive view of KPIs and facilitated data-driven decision-making.\u00a0<\/span>\u00a0<\/span><\/p>\n

This enhanced visibility empowered the operations team to develop actionable plans that drive continuous improvement and surpass their operational objectives. With more detailed reports that offer greater accuracy, the automative supplier will be better able to gain actionable insights from their rapidly expanding IoT and mobile application data.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Migrated 550+ Tableau dashboards to QuickSight using EZConvertBI, achieving 80% automation, 60% time savings, and seamless collaboration under tight timelines and data constraints.<\/p>\n","protected":false},"author":2,"featured_media":4683,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[147,145,143,142,141,88,83,54,55,58,85,95],"tags":[],"class_list":["post-3872","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-amazon-quicksight","category-amazon-s3","category-apache-airflow","category-apache-hudi","category-aws","category-bi-reporting-visualizations","category-business-intelligence-insights","category-case-studies","category-industry","category-manufacturing","category-reporting-modernization","category-technology","entry"],"acf":[],"yoast_head":"\nAutomotive Supplier Enhances IoT Reporting 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