Munich Re, a global reinsurance company, was facing challenges in managing and utilizing its vast data resources. The company deals with complex risks, including natural catastrophes, satellite launches, and large building projects, which generate a significant amount of data. However, the company was struggling with data collaboration and transparency across its various departments and global locations. Different teams were working on similar data analytics projects without knowledge of each other's work. This lack of coordination and collaboration was hindering the company's ability to innovate and develop new products based on shared insights. Furthermore, the company was grappling with the challenge of efficiently managing its data lake, which contained thousands of data sources and tables. The difficulty lay in finding specific information and extracting it from the data lake.

Riot Games, the company behind the globally popular game League of Legends, was struggling to manage and derive value from the vast amounts of data generated by its over 150 million registered users. The company had a growing Databricks lakehouse on their AWS S3 cloud storage service, but finding valuable information within this data lake was proving to be a challenge. The analysts at Riot Games needed the right data to derive insights using their Tableau business intelligence platform, but the engineering teams were constantly bogged down with questions about the data. The engineers were repeatedly answering the same questions, which was taking up valuable time that could have been spent on more meaningful projects. The company needed a solution that would allow analysts to self-serve and self-educate, reducing the burden on the engineering teams.

Crocs, Inc., a global leader in innovative casual footwear, has been experiencing accelerated sales growth and setting high revenue targets. This growth led to an increased focus on data and analytics across all areas of the enterprise, including finance, digital, operations, supply chain, and more. However, managing disparate data sets across different systems became a challenge. To manage this data proliferation, Crocs invested in cloud-based infrastructure and technology, including a Snowflake data warehouse on the Microsoft Azure cloud platform and expanded their use of the Microsoft Power BI platform. Despite these advancements, Crocs recognized the need for better data governance to provide valuable insights and facilitate decision-making. An internal audit team identified several opportunities where data governance would provide value, leading to the creation of a data governance team.

Airlines Reporting Corporation (ARC), a key intermediary in the travel industry, had accumulated a massive amount of data over its 50 years of operation. This data was stored in on-premises servers and was largely siloed by the company’s seven business domains. The company wanted to bring new products to market faster by making data more accessible across the business. However, ARC's existing product development processes relied heavily on the tribal knowledge of domain experts, which created bottlenecks and risked loss of expertise when employees left the company. In 2018, ARC decided to embark on a digital transformation initiative, which included modernizing business processes and migrating all their data to an AWS S3 Data Lake and Snowflake Data Cloud. The goal was to make data more accessible across domains and reduce reliance on individual expertise during product development. To ensure that employees could find the data they needed, ARC sought to implement a data catalog solution for their migrated cloud data.

Fifth Third Bank was facing a challenge in sharing and managing data across the organization. The bank needed a platform that could enable teams across the organization to use data to drive innovation and deliver superior customer engagements and outcomes. The lack of a centralized system for cataloging, tagging, governing, and sharing data was creating inefficiencies and slowing down the speed of operations. Furthermore, the bank needed to improve the security of its data management. The challenge was to find a solution that could provide a single source for data that could be easily accessed by data scientists, analysts, and engineers.

Vattenfall, a Swedish power company operating in multiple European countries, is committed to achieving fossil-free living within one generation. This goal requires the company to decarbonize electricity production and collaborate with partners in other industries, such as steel production. However, the company faced challenges due to the complexity of its operations across different energy sectors and countries. For instance, wind energy produced in the Netherlands could be used to produce hydrogen for Swedish steel, requiring constant communication and data sharing. However, siloed data within Vattenfall hampered this level of collaboration. Furthermore, day-to-day operations like equipment performance evaluation and maintenance planning required extensive data insights. Vattenfall also had to comply with regulations in multiple countries and the European Union, including the General Data Protection Regulation (GDPR), nuclear regulations, and other government reporting requirements. Failure to comply could result in fines in the millions of Euros. Vattenfall needed to improve its data governance to comply with these regulations and to facilitate enterprise-wide collaboration.

FLSmidth, a multinational engineering company based in Denmark, faced significant challenges in managing its data assets due to its size, history, and the complexity of its data environment. The company, with nearly 12,000 employees worldwide, has been growing for over 130 years, with numerous acquisitions adding to its data complexity. Each acquisition brought in new systems and data assets, which were not readily available to everyone who might need them. Additionally, valuable tribal knowledge often got lost when employees left the company. These complexities posed significant roadblocks to achieving the company's top-line goals of creating a data-driven enterprise and turning data assets into revenue-generating resources.

MercadoLibre, the largest online commerce and payment ecosystem in Latin America, faced the challenge of democratizing information across the company. The company wanted to provide its employees with easy access to data and enable them to run queries independently, without the need for constant IT involvement. However, this posed a risk of losing data governance, as analysts were given complete independence to use tools like Tableau. The company needed a solution that would allow controlled freedom, ensuring that employees could access the right information and data, while maintaining data governance.

Parexel, a global provider of biopharmaceutical services, faced significant challenges in leveraging big data to transform their operations. The company had been approaching the issue as a technology problem, underestimating the complexity of the clinical development process and the importance of domain expertise. The business was focused on understanding the value and impact of treatments in the real world, which required the use of real-world data and healthcare data. However, the company's data governance was fragmented, and they had to build a capability in real-world data that was adjacent to their own business data. Additionally, the company was funding initiatives to advance their business operations and analytics capabilities, but the gap between their corporate IT function and the business was wide, with IT drifting away from the business.