{"id":3869,"date":"2024-11-13T07:00:30","date_gmt":"2024-11-13T07:00:30","guid":{"rendered":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/?p=3869"},"modified":"2025-11-15T05:57:11","modified_gmt":"2025-11-15T05:57:11","slug":"international-manufacturer-leverages-bi-analyzer-to-guide-data-product-strategy","status":"publish","type":"post","link":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/case-studies\/international-manufacturer-leverages-bi-analyzer-to-guide-data-product-strategy\/","title":{"rendered":"International Manufacturer Leverages Wavicle\u2019s BI Analyzer to Guide Data Product Strategy"},"content":{"rendered":"<p><span data-contrast=\"none\">This international paint manufacturer was struggling to manage its disorganized and fragmented data environment that had accumulated from years of rapid growth and acquisitions. With more than 250,000 reports spread across multiple BI platforms\u2014including Tableau, MicroStrategy, and SAP Business Objects\u2014the company\u2019s data landscape had become difficult to manage, making it challenging to identify valuable data assets for strategic use.<\/span><\/p>\n<p><span data-contrast=\"none\">Knowing they wanted to develop a decentralized data strategy and start by focusing on key data products and domains, the company turned to Wavicle for guidance. They needed assistance identifying the high-impact data domains where this transformation should begin. Using Wavicle\u2019s BI analyzer to automate evaluation of data use within their BI systems, the manufacturer aimed to gain a holistic view of their BI environment and their most-used data assets to inform the design of a decentralized data framework that would support their future data and analytics initiatives.<\/span><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">Challenges in managing the fragmented data environment<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"none\">The paint manufacturer saw a valuable opportunity to develop a decentralized data environment that could empower specific business domains \u2013 like sales, finance, and marketing \u2013 with direct access to the insights they need for success. However, without a clear roadmap or a sense of data priorities, starting on this type of digital transformation was daunting.<\/span><\/p>\n<p><span data-contrast=\"none\">The manufacturer had accumulated a disjointed and complex data landscape due to rapid expansion and numerous acquisitions. With data scattered across Tableau, MicroStrategy, and SAP Business Objects, the company struggled to gain a holistic view of their own data and its usage patterns.<\/span><\/p>\n<p><span data-contrast=\"none\">The company turned to Wavicle, seeking help to gain clarity on their data assets. By leveraging Wavicle\u2019s BI analyzer solution, along with insights from Wavicle\u2019s consultants\u2019 deep analysis of Tableau, MicroStrategy and SAP BO reports, they aimed to gain a comprehensive view of their data assets and understand which metrics and data domains had the greatest impact across the company. Using this intelligence, they partnered with Wavicle to prioritize critical data assets and domains in order to strategically transform their data ecosystem and fuel their business objectives.<\/span><\/p>\n<h2><span data-contrast=\"none\">Wavicle\u2019s BI analyzer turns data chaos into clarity\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"none\">The paint manufacturer partnered with Wavicle to execute a comprehensive, enterprise-wide data discovery and prioritization project.<\/span><\/p>\n<p><span data-contrast=\"none\">Wavicle\u2019s team began by building a comprehensive inventory of BI assets, ensuring that key reports across platforms were accurately accounted for and scoping a targeted set of 48,000 reports across the company\u2019s three BI platforms for detailed analysis. Using Wavicle\u2019s proprietary BI analyzer, Wavicle automated the extraction of essential metadata from the reports, delivering valuable insights into report structure, usage patterns, relevant KPIs and metrics, and dependencies. By thoroughly analyzing these assets, the team provided the manufacturer with a clear and actionable understanding of its current data environment.<\/span><\/p>\n<p><span data-contrast=\"none\">After this inventory was established, Wavicle mapped each BI asset under functional domains and grouped the attributes of prioritized BI assets under master domains. This was a crucial step in ensuring that the data assets were aligned with the company\u2019s core business operations such as sales, finance, and marketing, using the company\u2019s existing domain taxonomy to ensure consistency and alignment. The team meticulously analyzed usage data, identifying high-impact master and functional domains based on factors such as the most-viewed and frequently accessed reports. This granular analysis allowed Wavicle to group BI assets according to their relevance within these domains.<\/span><\/p>\n<p><span data-contrast=\"none\">Wavicle\u2019s efforts in organizing and mapping the data played a crucial role in enabling the company to plan its data strategy and prioritize the data assets that need to be addressed first when building a decentralized, data product-driven architecture.<\/span><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">Improved efficiency in data management<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"none\">Wavicle rapidly analyzed the paint manufacturer\u2019s data across multiple BI platforms and mapped and prioritized relevant data domains to support a strategic shift toward a decentralized data architecture. The team meticulously documented the assets across these platforms, providing valuable insights into how each asset was associated with the company\u2019s functional business domains and helping them strategically launch a new, modern data strategy.<\/span><\/p>\n<p><span data-contrast=\"none\">A pivotal component of this project was Wavicle\u2019s BI analyzer, which facilitated the analysis of 48,000 reports and more than 50,000 attributes to identify 571 unique and frequently used metrics and map those to relevant domains. The tool streamlined the process of metadata extraction and usage analysis across multiple BI platforms, enabling the team to gain quick insight into the structure and performance of the existing data assets. This automated solution significantly reduced the time required to assess the BI landscape and identified usage patterns that enabled the prioritization of data assets based on their business impact.<\/span><\/p>\n<p><span data-contrast=\"none\">In just 10 weeks, Wavicle\u2019s team mapped and prioritized the manufacturer\u2019s data assets, empowering the company with the insight necessary to strategically develop their new, decentralized data architecture, starting with the implementation of domain-specific data lakehouses. By providing clear direction on where to focus their efforts for maximum impact, Wavicle helped this manufacturer set the stage for long-term growth through enhanced data and analytics capabilities.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>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":4680,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[87,83,54,72,58,113,102,73,99],"tags":[],"class_list":["post-3869","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-analytics","category-business-intelligence-insights","category-case-studies","category-data-management","category-manufacturing","category-microstrategy","category-sap-business-objects","category-data-strategy-assessments","category-tableau","entry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Manufacturer Drives Data Strategy Using BI Analyzer<\/title>\n<meta name=\"description\" content=\"Discover how an international manufacturer optimized product strategy powered by 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