Big Data is a generic term that describes a large volume of data. However, in the context of data analytics, artificial intelligence, and machine learning, Big Data refers to a large set of data that is analyzed by a set of technologies to reveal patterns or trends. The proliferation of the Internet and specifically cloud services is directly responsible for the growth in Big Data. In the past, data was created in smaller volumes in isolated environments for specific purposes. Today, large sets of data are available for public consumption thanks to the digital disruption brought about by social media, the Internet of Things (IoT), and other online-based software applications which have created vast amounts of publicly accessible data. A Big Data solution needs a variety of different tools which range from technologies dealing with data sources, integration, and data stores, to technologies that help with the creation of data models, presenting these through visualization and reporting. We are joined by Rukmani Gopalan, Principal PM Manager at Microsoft, to get her thoughts on implementing cloud solutions, where they can contribute. What types of issues are giving you troubles as you adopt a more diverse data ecosystem? Microsoft Azure has a comprehensive offering covering all requirements needed to build and manage a Big Data solution. Building this solution on Azure requires the deployment of a suite of complementary product technologies which integrate seamlessly and collectively to create a comprehensive Big Data offering.