The biopharma company was experiencing rapid growth and was looking for ways to leverage data to improve sales, patient engagement, and treatment. However, the company's extract, transform, and load (ETL) processes required a prohibitive amount of development time, especially at the transformation stage. This made it challenging and time-consuming for stakeholders to access data from the different sources, which included a Netezza data warehouse, a CRM in the cloud, google analytics, and other 3rd-party data sources. The company realized that it needed a real-time, 360-degree omnichannel view of patient data across the different sources. In addition, the company was interested in enabling its human resources department to gather data from SuccessFactors and run its own reports on diversity and resource allocation, but the data infrastructure could not support this. The company also felt challenged in its ability to easily manage the lifecycle of documents for regulatory reporting.

The Company, a leading construction equipment manufacturer, was facing challenges due to sluggish sales and competition from low-cost alternatives. The Company's customers were demanding high returns on their investments with minimum downtime and maintenance. To meet these demands, The Company needed to optimize asset performance and reduce machinery part breakdown in the field. The Company had invested in modern tools and technologies for telematics and predictive analytics, and in field sensors and big data technology. However, the field equipment data needed to be analyzed constantly in real time against the backdrop of service life records, warranty data, and other information. Traditional data integration methods were proving to be slow and expensive. The Company needed an agile data integration and access layer that could easily integrate big data with other sources of enterprise or cloud data in real time.

Coca-Cola Peninsula Beverages faced a challenge of multiple disparate data sources in various locations, which required lengthy and costly ETL solutions and extensive manual workarounds to extract meaningful information and reconcile this data to their ERP systems. The company needed fast, user-friendly access to integrate and report on data from various sources to optimally manage its business within an economically challenging environment. The typical daily update processes could take up to eight hours just for one day’s data, and that could fail, leaving the business without up-to-date reporting.

LeasePlan, a global leader in Car-as-a-Service, was transitioning from an analog business model to a fully digital one. As a car-as-service company, LeasePlan collects a large amount of behavioral data, marketing data, traffic information, social media information, and services and maintenance data. All this data needed to be integrated and contextualized for business decision-making and optimizing business services. However, being a globally distributed company, LeasePlan had data spread across a variety of siloed and heterogeneous data sources (SAP, Salesforce, IBM DB2, Snowflake, etc.), making data integration and data delivery challenging for sound business decision-making, optimizing processes, creating new business models, and complying with EU regulations. LeasePlan aspired to become a fully digital car-as-a-service company by expanding its service portfolio and encouraging revenue-generating activities through innovative products and services. Achieving this required the creation of a unified Global Data Hub, to act as a single source of truth of high-quality data for the whole company, and to support proactive and reactive data initiatives.