Visteon Corporation, a leading global automotive supplier, was facing the challenge of streamlining the retrieval of critical data from a variety of ERP systems, legacy environments, and disparate databases for business users. The company was using four different enterprise resource planning (ERP) systems in North America, each creating distinct types of data. Users previously had to log in to each system, gather the data they required, and then manually combine it to generate reports. This process was time-consuming and inefficient. Additionally, the company wanted to create new types of financial reports for employees and supply chain partners.

WESCO International Distribution, a large, geographically dispersed company with 350 warehouses, 6,000 employees, 200,000 products, and more than 130,000 business customers worldwide, faced the challenge of centralizing decision-making and rolling up information in a timely manner. The company's aging information systems were due for an upgrade as they were not user-friendly and required assistance from professional analysts to execute many of the reports. Furthermore, the complex reporting infrastructure required database administrators to follow a tedious process to prepare the data for reporting, which took a significant amount of time. The company needed a Web-based solution that could automatically roll up and distribute reports to users in any format.

The Charlotte-Mecklenburg Police Department (CMPD) had been collecting data on criminal activity for many years. However, it relied upon a manual process of sifting through 13 disparate data sources to analyze crime statistics, identify trends, and model resource allocations. This made it difficult to make sense of all the information. Users typically had to run multiple queries to be able to drill into the data and answer specific questions. CMPD command staff recognized the need for improvement and sought funding through an Urban Area Security Initiative (UASI) Homeland Security Grant. The goal was not only to enable command staff and dispatchers to easily run reports, but also to push information out to officers in real time.

RCM Brain needed a flexible analytics solution with comprehensive data management, data visualization, and predictive analytics capabilities that could be embedded into a larger software platform. The revenue cycle management (RCM) process that medical providers use to track revenue from patient visits is complex and error-prone, leading to high administrative costs and revenue leakage. RCM data is spread among various systems, making it difficult to create comprehensive reports. The challenge was to automate this process and reduce the costs associated with inaccurate medical claims.

Link Market Services (LMS) faced the challenge of producing over 4,000 complex internal and client ad hoc and management reports every day from two Oracle transaction databases containing up to 1.8 billion rows of data. The company needed a solution that could deliver rapidly, as they wanted to be independent from a competitor as soon as possible. The solution had to be able to connect to a wide variety of data sources and consolidate information into a single report. The company also required a solution that could produce reports as soon as a client comes on board, and deliver these reports instantly.

In a world of shrinking budgets and rising rates of chronic disease, health information exchanges (HIEs) are an essential element of national and regional efforts to improve healthcare and contain costs. HIEs establish an interoperable framework for healthcare providers to share secure patient information across disparate electronic health record (EHR) platforms and other information systems. However, the challenge lies in creating a flexible, reliable, and scalable analytics platform that could ingest large volumes of diverse data types and provide high performance for batch and interactive processing. Since healthcare providers face steep penalties if they fail to secure protected health information (PHI), the solution also required a robust security architecture that could keep pace with interactive performance requirements as deployments grew.

Smartlogic was looking to support the knowledge management needs of a broader audience and provide an efficient and economical platform for customers and partners. They explored a number of cloud deployment options for their Semaphore platform. The solution needed to have full functionality and integration capabilities, enterprise-grade security, high availability and scalability, all while keeping overall costs and environment management low. They aimed to bring together three leading technologies to provide an efficient and economical platform for customers and partners to address security, scale and on-demand requirements.

The Bank, a major player in the derivatives market, was struggling with a legacy system that was slow, inefficient, and unable to deliver real-time alerts to manage market and counterparty credit positions in the desired timeframe. The existing system, based on a relational database, was comprised of multiple installations around the world, leading to duplicated, redundant, incomplete, and inconsistent data. This made risk management fallible and time-consuming, and the Bank recognized the importance of having a real-time global view of its positions.

The national postal service was facing a significant decline in traditional mail volume due to the rise of electronic delivery. They needed to evolve their business model to stay relevant in the digital age. They saw potential in APIs to monetize their valuable demographics data and offer new business services. However, their initial attempts to develop APIs were slow and lacked the necessary tracking and management features. They needed a solution that offered advanced design capabilities, easy integration with backend services, and scalability to support a growing number of consumers.

TiVo, a pioneer in home entertainment, faced a challenge as its growth continued to accelerate and new partners came on board. The company's infrastructure included over 40 web services that provided services for both TiVo and its partners. Prior to implementing Mule, TiVo integrated these web services in a point-to-point fashion using custom Java code. As the number of services increased, the infrastructure grew in complexity, becoming more and more brittle. Every new service required an exorbitant amount of development effort and was difficult to maintain. Even simple configuration changes presented a problem - because of all the dependencies introduced by the point-to-point architecture, any change to the system would trigger changes that cascaded throughout the application. Because of the complexity, developers would need to meticulously test the entire system, making sure that the change didn’t have unintended consequences.

UCSF Medical Center, one of the nation's leading academic medical centers, was previously using a homegrown paging system for communication among its 8,000 staff members. The system was robust, but it had its drawbacks. Communication was one-way and text-based, requiring doctors to call back for additional information, slowing the flow of information and response to patients. It was difficult to coordinate across care teams as messages were not saved for future reference. Finally, team members had to carry a pager around with them in addition to their mobile devices, which was cumbersome and expensive.

Citrix, a pioneer in virtual workspace solutions, was looking to create agility and competitive advantage by pragmatically moving their primarily on-premises infrastructure to the cloud in phases. The first opportunity came from the marketing department. The Citrix marketing team needed a better way to synchronize data between Marketo and Salesforce. Client account data wasn't always up to date, hampering the pace of sales and the ability of the marketing team to use real-time data to refine their marketing efforts. Vinod Sangaraju, Integration Development Manager for Citrix, knew that an on-premises only solution would not scale with their long term vision to move to the cloud.

Tic:Toc, an Australian fintech company, was launched with the aim of transforming the traditional home loan process. The company wanted to eliminate the inefficiencies in the home loan approval and fulfillment process, allowing customers to easily submit loan applications online and receive instant decisions. However, the challenge lay in the complexity of the traditional process. For instance, validating a property purchased via a home loan involved multiple steps and parties, making it a time-consuming process. To provide customers with a seamless, instant home loan application experience, Tic:Toc needed to integrate data from various sources, offer real-time document generation and home loan decisions, and deliver their new product to market quickly to gain a competitive advantage.

Salesforce, a global leader in CRM, has grown rapidly over the years, acquiring over 70 companies. This growth has resulted in thousands of systems and massive amounts of data. The company had leveraged MuleSoft's Anypoint Platform well before acquiring the company. After the acquisition, Salesforce initiated an effort to adopt API-led connectivity to better integrate systems and data, aiming to provide connected experiences to their 150,000 customers and 49,000 employees. The company wanted to move away from point-to-point connectivity to unlock and integrate critical data across the enterprise, create a single view of their employees, automate manual HR processes, and integrate Salesforce customer accounts with the accounts of acquired companies to build a 360-degree customer view for sales teams.

The Yassa Lab at the University of California, Irvine (UCI), led by Dr. Michael Yassa, was facing several challenges. They were struggling with managing multi-center collaboration involving the collection of large data sets, quality control, analysis, and submission to NIH databases. The growing data and analytic complexity were impeding data reuse and scientific reproducibility. They were also looking for ways to best support and collaborate with other labs in the UC Irvine community. The lab was involved in a multicenter collaboration studying biomarkers of Alzheimer's disease in Down syndrome, which required secure sharing and processing of a variety of data.

Consumer debt was rising in Brazil, and it was becoming challenging for both consumers and debtors to find solutions. The target market of debtors and the ensuing volume of data to be analyzed were both large and therefore, challenging. Acordo Certo had a small team of data scientists, who were using traditional methods to collect and analyze data, as well as to build and deploy predictive and scored models. However, due to the large database of customers, there was a need to increase the agility of model development and accuracy, as well as improve overall trust in AI by making the results of machine learning algorithms transparent to business partners, such as retailers and banks.

HJ Machine and Pattern, a machine shop that provides solutions for complex problems, was in need of an update. The company's phone system and computer design had not been updated for a few years. When Gurjinder Jammu took over as President and CEO, he decided to modernize the company's operations, including its ERP software. The company considered several ERP software options before settling on E2 in 2017. The decision was based on the simplicity of E2 and its efficient information flow. However, in mid-2020, the company decided to upgrade to E2 SHOP on the cloud.

Stainless Metals, a custom fabrication shop, was facing challenges in tracking jobs on the shop floor and estimating jobs. They occasionally lost track of a job, and they lacked an efficient system for estimating jobs. They decided to implement E2 SHOP on the cloud to address these issues. However, the COVID-19 pandemic hit shortly after they got E2 SHOP in March 2020, which delayed their plans.