The San Francisco Municipal Transportation Agency (SFMTA) faced significant challenges in managing and analyzing the vast amounts of data generated by its operations. The agency's traditional reliance on relational databases and middleware was proving inefficient and resource-intensive. The existing systems required extensive manual processing, such as pulling data from CSV files into Excel for analysis, which was time-consuming and labor-intensive. Additionally, the on-premises infrastructure demanded costly engineering hours for maintenance and upgrades, making it difficult to scale and adapt to the growing data needs. The SFMTA recognized the need for a centralized data management solution that could streamline processes, reduce administrative bottlenecks, and enable data-driven decision-making to improve transportation services and optimize revenue.

Five years ago, Jacksonville University (JU) faced significant challenges in accessing and utilizing data effectively. The process was cumbersome, requiring leadership to fill out forms and wait for the analytics department to provide static reports. This reactive approach hindered timely decision-making and limited the ability to leverage data for strategic purposes. The arrival of President Tim Cost in 2013, with his extensive experience in Fortune 500 companies, brought a new expectation for technology and data accessibility. The need for a more dynamic and proactive data culture became evident, prompting JU to seek a solution that would democratize data access and empower leaders, faculty, and staff to make informed decisions. The existing data processes were siloed, with different departments owning separate data sets, leading to inconsistencies and inefficiencies. Meetings with deans often resulted in conflicting data interpretations, as each department relied on its own data sources. This lack of a unified and authoritative data set hindered meaningful discussions and strategic planning. The challenge was to create a centralized and accessible data platform that would streamline data access, improve data accuracy, and foster a culture of data-driven decision-making across the university.

Rolls-Royce, a leading British brand in the manufacturing industry, is facing the challenge of transitioning to a net zero carbon future. The company recognizes the need to decarbonize rapidly to ensure its longevity and continue delivering excellence in its engine manufacturing. The challenge is compounded by the vast amount of flight data that needs to be processed and analyzed to optimize carbon output. The existing on-premises infrastructure was insufficient to handle the data volume and processing power required for this task.

Kinleigh Folkard & Hayward (KFH) faced the challenge of modernizing their IT infrastructure while ensuring robust security and mobility. With sensitive information across ten business divisions, the leadership was initially hesitant about cloud adoption. However, by 2018, their on-premises infrastructure was nearing end-of-life, prompting a reevaluation. The COVID-19 pandemic further disrupted their plans, necessitating a rapid pivot to remote work solutions. The need for effective communication and collaboration tools became paramount as lockdowns were announced, pushing KFH to fast-track their digital transformation efforts.

Most businesses generate a lot of data, but that data isn’t valuable for decision making if it’s not structured and analyzed. Analytics aren’t as effective if they are slow and expensive to produce. Inlitix was founded to offer a timely, easy-to-use, affordable BI as a service for small and medium-size businesses. They focused on interoperability across different ERP systems with different datasets and offered out-of-the-box reporting and analytics solutions. However, Inlitix found that it only needed more compute power at certain times, such as when it spins up development and QA environments or when production data is refreshed. It didn’t make sense to pay for a constant high level of compute resources during the times when they weren’t needed. To minimize the company’s compute requirements and maintain affordability, staff would manually adjust and optimize queries, which took time away from focusing on more strategic tasks and adding value to their application. Inlitix wanted to optimize the balance between cost and performance of its databases while ensuring it could quickly process data from customer ERP systems and refresh Power BI reports more frequently.

Intesa Sanpaolo Group, Italy's leading banking group, faced the challenge of improving its real estate operations and facility management to cut waste and reduce its environmental footprint. The bank manages thousands of buildings and is one of the largest real estate owners in Italy, with more than 40 million square feet of assets. The challenge was to reduce energy consumption, improve comfort, and optimize operational efficiency across its vast real estate portfolio. The bank needed a solution that would provide real-time visibility into HVAC and other systems in its buildings, enabling data-driven actions to be taken. The complexity of the bank's environment required a robust and secure solution, as data protection is a critical concern for the bank.

The demand for transparency across investments, to align with the SDGs, meant the company needed to augment financial performance figures with ESG performance. This would ensure every investment decision would be fully informed, and that every retail and institutional client could gain a holistic view of each fund’s performance in terms of sustainability and profitability. The company was clear from the outset that it required a partner who could bridge the gap between IT and its business and rapidly deliver a solution to meet its internal deadline.

The Dorset healthcare system faced significant challenges in integrating and analyzing data from various sources due to the complex setup of multiple organizations. Information was siloed across the county's healthcare networks, making it difficult to collaborate and derive insights. The need for a unified data warehouse was identified to enable better decision-making and improve patient care. The COVID-19 pandemic further highlighted the urgency of having a robust data infrastructure to respond effectively to emerging healthcare challenges.

When the COVID-19 pandemic hit, educational institutions worldwide faced unprecedented challenges. The University of South Florida (USF) was no exception, as it had to quickly adapt to the new reality of remote learning and collaboration. The university, with its multiple campuses and a large student body, needed a solution that could facilitate seamless communication and learning without compromising the quality of education. USF had already been in the process of transitioning to a unified technology environment, but the pandemic accelerated this need. The challenge was not only to continue educational activities but also to ensure the safety and health of students and faculty, particularly in the medical field where hands-on training is crucial.

CCBPI recognized the need to integrate and automate its data processes to enhance operational efficiency and maintain data transparency. Previously, Power BI reports were generated using data from manually edited Microsoft Excel files, which involved multiple users and steps prone to human error. The leadership team, led by CIO Winnie Talosig-Rebancos, identified the automation of report creation as a critical component of their digital transformation strategy.

For a city the size of Laval, managing the 311 system, which fields questions and complaints about non-emergency issues, can be a significant challenge. The city handles an average of 645 calls a day, and when including in-person requests and emails, the 311 operators respond to more than 250,000 requests annually. The manual recording of each call can sometimes be left incomplete, leading to inefficiencies. The push to augment the system with AI began in 2019, with the goal of adding value for each person contacting the 311 system. The city was already using Microsoft 365, making the adoption of Dynamics 365 and Azure a simpler process. However, a multivendor survey was conducted, including the creation of AI assets through open-source technologies. The goal was to create a high level of interoperability between Azure and the existing Microsoft 365 environment, simplifying the development of a solution using Azure AI capabilities.

The New York City Department of Environmental Protection (DEP) faced challenges in managing the increasing call volumes at their IT and HR service desks, which were only staffed during regular business hours. This led to longer response times and reduced employee satisfaction, particularly for after-hours requests such as password resets. The agency needed a solution to provide 24/7 support to its 6,000 employees, who operate in a 24/7/365 environment, including plant operators and those responding to emergencies like water main breaks. The goal was to improve user experience and drive operational efficiencies by providing continuous availability of services.