One of the main challenges was that the company required a centralized data warehouse for unified reporting and analytical requirements. The data was not consolidated properly and its structure was not suitable for user requirements. Besides, reporting process was extremely slow. Individual systems had expanded to the point that information was no longer stored and presented in the centralized manner that could facilitate efficient organizational decisions across the company as a whole. It was also becoming obvious that a data warehouse should better enable internal and external user access to data and increase the performance of analysis and reporting activities. To evolve its offering from simple data feeds to self-service BI, the company needed a new robust platform that could enable users come out of excel mindset and could take them to exploratory mode for better and faster decision making. The objective was to integrate the line of business applications (On-Premise and SAAS).

The case study revolves around the challenge of digital transformation faced by many organizations. In the rapidly evolving digital landscape, businesses are under constant pressure to adapt and innovate. They need to increase their business agility, improve customer experience, and lower the total cost of ownership. However, the process of digital transformation is complex and fraught with challenges. It requires a deep understanding of technology, a clear vision for the future, and the ability to execute effectively. The challenge is not just about adopting new technologies, but also about changing the way businesses operate and deliver value to their customers.

In the rapidly evolving digital landscape, organizations are constantly seeking ways to unlock new opportunities and accelerate their digital transformation. The challenge lies in increasing business agility, improving customer experience, and reducing the total cost of ownership. Traditional methods and technologies often fall short in meeting these demands, creating a need for innovative solutions that can drive transformational goals with pace and passion.

The customer, a global leader in materials engineering solutions, was facing a challenge in managing the increasing number of queries from its employees. The company's help desk team was overwhelmed with the volume of tickets created in Service Now, which was impacting their productivity and increasing support costs. The company needed a more streamlined approach to facilitate their employees and users to avail information from their help desk team. The challenge was to reduce the number of tickets hitting the help desk without compromising the quality of service. The company identified the need for a well-trained conversational bot that could automate responses for FAQs leveraging the power of Artificial Intelligence (AI), Natural Language Processing, and Cognitive Services.

The customer, a leading American multinational software firm, was facing significant challenges with their existing Big Data platform. They had initially created a solution using the Hadoop Map Reduce engine and Hive Queries (HQL), but this setup was proving to be inefficient. The main issues were slower code execution speed, higher storage requirements, and difficulty in maintaining workflows. These issues were impacting their business performance and slowing down their digital innovation. As part of a multiyear initiative, the company was planning to move their Big Data platform from Cloudera Hadoop On-Prem instance to Cloudera Data Platform (CDP) on Azure. The first step in this process was to explore the prioritized MapReduce jobs in the current state and consider migrating them to Spark to reduce execution and processing time.