The impact the cloud is having on big data and advanced analytics is shocking. We've hit a go public or go home situation – and while many enterprises I've spoken to about this migration are still on the fence, they understand they need to invest in more public cloud to engage with empowered customers. The problem is many are struggling with organizational momentum and regulatory issues that often manifest in technical objections that don't hold water. Public cloud was the number one priority for big data in 2016. Because firms are running into a cost wall as they scale out their one premise infrastructures.
It is safe to say that even before the impact of the COVID-19 pandemic hit; companies had begun a steady march into the cloud. Then, with the events of this year, we have seen an incredible surge in demand for remote technical services and an overload of data compiling on application platforms. These increases are leading organizations of all sizes to seek larger, flexible, and secure platforms to support the rapid, immediate growth and propel their companies into the future. Earlier this summer, Gartner predicted public cloud services would grow 19 percent just this year, despite also acknowledging the impacts of COVID-19 would cause overall global IT spending to decline eight percent in 2020. With this rapid growth, companies making quick transitions to the cloud can overlook or miss key learnings and vital steps that can guarantee a successful cloud migration.
In this course, we would explore various Cloud Migration tools and services available on Microsoft Azure Cloud Platform. We will learn what are the various kinds of Migrations including Database Migration, Physical Migration from On-Premise Data Center to the Cloud, from Cloud to On-Premise, between different cloud vendors such as Microsoft Azure, Amazon Web Services (AWS), IBM Bluemix, etc. We would also explore Recovery and Backup options with Site Recovery. Throughout the course we would cover following Migration services offered by Microsoft Azure- Site Recovery, Database Migration, Azure Migrate, DataBox, Data Box edge and Data Gateway. We would be learning concepts and methodologies with practical exercises.
Many companies are moving their legacy data warehouse to the cloud for a variety of reasons such as cost savings, scalability, use of data analytics for business growth, and improved integration. Spotify, an audio streaming platform, moved to Google Cloud Platform (GCP) in 2015 to handle its massive data and free up its developers to focus on innovation. With the help of a dedicated Spotify/Google cloud migration team, they migrated successfully and increased scalability. Etsy, a global e-commerce platform, was looking to improve its UX and site performance. They chose to migrate to GCP in 2018 and used a hybrid environment to execute the migration.
Earlier this year, the UK-based bank TSB attempted a major IT migration, a massive project several years in the making. The result was a complete and utter fiasco. Customers were unable to log into their accounts. Data from some customer accounts appeared in different ones. Obscure technical error messages abounded.