Animex Foods, one of the largest meat producers in Poland, faced a significant challenge in maintaining its processing plants' reliability to maximize productivity. The company, with over 11,000 employees and twelve plants, had a robust digital process and advanced data analytics supporting its business operations. However, as the company grew, it reached a point where it needed to add storage capacity. Its existing storage infrastructure could not be expanded, and the storage arrays had become too slow to support the fast-paced business effectively. The company needed a solution that could ensure continuous business operations, increase plant reliability, and maximize production output.

Armedia, a veteran-owned systems integrator specializing in digital transformation, IT modernization, and enterprise content management (ECM) solutions, was seeking to optimize its clients' complex digital transformation initiatives and case management workflows. The company, which serves both public and private-sector organizations, including U.S. government agencies, education, transportation and logistics, manufacturing, retail, finance, healthcare, and technology sectors, needed to provide real-time, actionable insight on demand. Armedia frequently recommends its own case management solution, ArkCase, which integrates ECM, business process management (BPM), and customer relationship management (CRM) functionality into a single platform. However, to take its solution to the next level, Armedia looked to embed reporting and analytics capabilities into the ArkCase platform.

Badan POM, the Indonesian Food and Drug Authority, was facing significant challenges with its legacy system. The authority, which regulates the country's registration and distribution of drugs, food, cosmetics, and health supplements, had large data storage requirements. The legacy system was causing slow system performance, leading to longer lead times needed to process license applications. This inefficiency was not only affecting the authority's operations but also its customer service. Additionally, the lack of adequate data protection was putting the authority's data and business at risk. The challenge was to improve the slow application performance and increase data protection.

Bartle Frere Bananas, a mid-sized, multi-generational farm in Far North Queensland, Australia, was on a mission to improve environmental outcomes and productivity for Australia’s horticulture sector. The farm, which supplies small markets and major grocery chains alike, was facing challenges related to extreme weather systems, flooding, and rising operational costs. The owner, Gavin Devaney, was committed to farming responsibly and sustainably, which meant balancing fertilization, irrigation, and productivity while being good stewards of the land. The farm wanted to gather data from across its operation and generate insights to inform best management practices, productivity, regulatory compliance, and sustainability. Devaney wanted to prove that his operations adhered to the farming industry’s best management practices and demonstrate that the bananas at Bartle Frere Bananas are carefully grown in a more innovative and sustainable way.

Bing Lee, a consumer electronics retail chain in Australia, was facing a significant challenge in integrating business data during a complex digital transformation project. The company's legacy ERP had become a highly customized system, dependent on a single point of failure. Its data was unstructured, and problematic processes were making the data generated by the system unreliable. Bing Lee invested in a new cloud-based ERP and developed their own Point of Sale (POS) system. A new reporting tool was also selected to improve user experience for employees. However, the transition to the new ERP was slowed down by the Covid-19 pandemic, and the company's sales and number of transactions substantially grew, increasing the volume of data through its systems.

Blechwarenfabrik Limburg GmbH, a leading manufacturer of tinplate packaging, was faced with the challenge of improving environmental sustainability and accelerating its manufacturing processes. The company, with 500 employees and locations in Germany, Denmark, and Poland, uses 22,000 tons of tinplate annually to produce 100 million canisters, cans, and bottles for chemical-technical liquids. Beyond sustainability, the company also aimed to streamline the processes and management of its subsidiaries by gaining new insights. The challenge was to enable standardized, integrated, real-time data analytics across all systems and departments to achieve these goals.

Hitachi Vantara had been providing on-demand storage services to automobile manufacturer BMW Group since 2012. The service was delivered by a 20-member operations and migrations team based in Munich, Germany, and supported all BMW Group production sites worldwide, including locations in Germany, China, and the U.S. However, the existing Hitachi storage platform was nearing its end of life, necessitating an upgrade to new hardware. The challenge was to carry out this upgrade without disrupting production continuity. The project was massive, impacting 12 sites in eight countries across four continents and involving 1,700 physical servers.

CBTS, an innovative IT managed service provider, was facing the challenge of meeting the increasing customer demand for cloud-based services. As a company that helps its customers achieve their business and IT goals with solutions that align to their cloud-first strategies, CBTS needed a flexible and reliable IT infrastructure. However, like its customers, CBTS wanted to avoid capital investment in infrastructure that might become redundant if customers scale-down. The company, which started as a division of a local telephony company, has evolved over the last 20 years and now works with more than 3,000 organizations across multiple industries. With 1,500 employees at locations in the US, Canada, the UK, Ireland, and India, the need for a cost-effective and agile cloud service solution was paramount.

Société Nationale des Chemins de Fer Luxembourgeois (CFL), Luxembourg’s national rail company, was faced with the challenge of improving customer experience and increasing efficiency by leveraging the vast amount of data generated by their trains and infrastructure. As one of the country's largest employers, with over 3,000 employees, CFL served 14.5 million passengers and transported 2.3 million tonne-kilometers of freight in 2020. The company needed to balance the management of track, rolling stock, station buildings, and other infrastructure with the needs of its passengers and freight customers. To explore emerging technologies like robotics, multimedia, unified communications, artificial intelligence, and the Internet of Things, CFL established a new department within its IT organization, known as Operational Technology. The challenge was to turn the large quantities of data generated by high-tech sensors and control systems into actionable insights with real business value.

Coop Group, a leading retail, wholesale, and food production company based in Basel, Switzerland, faced a significant challenge in managing its complex, fast-paced supply chain. The company, which operates almost 2,500 retail stores and generates annual revenues of CHF 30.2 billion (US$32.7 billion), needed to ensure high-quality fresh food was always available on store shelves and online. Efficiently handling the logistics around its 14 distribution centers was central to the retailer’s success. To ensure that customers could get essentials such as fruit, vegetables, and bread fresh every day, Coop relied heavily on data analytics and sophisticated forecasting. However, with growing data volumes, the company recognized the need to expand its data storage infrastructure to ensure timely logistics processes and smooth food deliveries.

DenizBank, a leading financial institution, was facing challenges in maintaining the customer experience and application performance as the bank expanded. The bank's customers demanded a fast, flawless, and customized experience, which required insightful data and scalable technology platforms. With the volume of customer data growing constantly, the bank needed a storage solution that was reliable, high-performing, and easy to manage. Additionally, DenizBank wanted to simplify their backup process. The bank was using over 1200 tapes per year for data retention, which was not only costly but also complex and time-consuming when it came to restoring data.

Disney Parks & Resorts are renowned for their fun, dynamic, and state-of-the-art experiences. However, delivering these seamless operations is a significant challenge, especially considering the complexity of Disney’s attractions. For instance, the Star Wars: Rise of the Resistance ride system requires real-time analysis and management of between 30,000 and 40,000 data points generated by Industrial Internet of Things (IIoT) sensors. Disney devotes extraordinary care to ensuring the availability and operating capacity of its attractions when guests are on site. This means maintenance must be planned and executed with precision to keep ride systems running flawlessly. The challenge lies in turning the massive amount of data generated into actionable insights for predictive maintenance.

Fannie Mae, a leading financial services company, was facing a challenge in managing its vast amount of business data. The company, which enabled the acquisition of more than 2 million home purchases and refinancings, and financing of approximately 598,000 rental units across the United States in 2022, was becoming increasingly digital and data-centric. To leverage all its business data across new and legacy applications, and to break down existing data silos, the company wanted to create an agile and dynamic enterprise data lake. However, the process of managing this data lake was complex and time-consuming. Every single one of its 15,000 datasets went through an initial registration process to assign a unique identifier, and every field had to be documented manually. This approach increased compliance and transparency but made the process slow due to the need to add an elaborate set of metadata to every dataset.

Gijima, one of South Africa’s leading ICT companies, faced a challenge with its inherited server and storage infrastructure. Much of the storage was reaching end-of-life, and Gijima recognized that upgrading could significantly improve performance and manageability. However, the company needed to migrate its data to new storage arrays without causing any disruption to its clients’ systems. Additionally, Gijima required a partner that could offer on-demand scalability at an attractive price-point, to cater to its wide range of clients, from enterprise clients to small to medium businesses. The company's state-of-the-art Tier-3 data center hosts business-critical systems for many of its biggest clients, making the need for a seamless transition to new storage arrays even more crucial.

Karolinska Institutet, a leading medical university, was tasked with accelerating research into chronic diseases and the impact of the human microbiome on reproductive health. This research was compute- and memory-intensive, requiring flexible compute capacity to process large batches of samples that arrive unpredictably. In 2020, the Centre for Translational Microbiome Research (CTMR) at the university was also tasked by the Swedish government to set up a new National Pandemic Centre (NPC) to strengthen Sweden’s COVID-19 response. The NPC was responsible for analyzing approximately 45,000 PCR-based COVID-19 tests per week, making it one of the largest lab facilities in Sweden for SARS-CoV-2 analyses. However, the CTMR was running IT services and analytics jobs on two physical servers, in a static configuration with no virtualization or capacity to scale, which posed a significant challenge.

La Sarine Health Network, a conglomerate of 12 publicly funded healthcare organizations in the La Sarine district of Switzerland, was grappling with the challenges of an aging population and the consequent complex healthcare demands. The organization relied heavily on digital systems for its service delivery, from back-office administration to managing patient data. However, their existing IT infrastructure, comprising two virtualized standalone servers with built-in storage, was proving inadequate. The servers were hosted at the region's residential care center and were unable to rapidly move virtual workloads from one platform to another, reducing flexibility and increasing the risk of downtime in a disaster-recovery scenario. Moreover, the onboard storage was nearing capacity, with utilization of around 85% on each server. The organization needed a solution that could offer quick and simple orchestration of storage as a single pool, allowing it to rapidly move workloads between servers and scale out its storage resources efficiently.