We recently sat down with Sandeep Uttamchandani, Chief Product Officer at Unravel, to discuss the top cloud data migration challenges in 2022. No question, the pace of data pipelines moving to the cloud is accelerating. But as we see more enterprises moving to the cloud, we also hear more stories about how migrations went off the rails. One report says that 90% of CIOs experience failure or disruption of data migration projects due to the complexity of moving from on-prem to the cloud. Here are Dr.

AWS Elastic Beanstalk is an easy way to deploy web applications and services. Just upload your code, and it handles the details like server provisioning, load-balancing, scaling, etc. In this article, Samson Omojola shows us how to deploy our Laravel apps to EBS.

Google Cloud has a genuine passion for solving technology problems that make a difference for our customers. With the release of our BigQuery Connector for SAP, we're taking a another big step towards solving a major challenge for SAP customers with a quick, easy, and inexpensive way to integrate SAP data with BigQuery, our serverless, highly scalable, and cost-effective multi cloud data warehouse designed for business agility.

From the modern application platform perspective, products should allow architects and DevOps teams to support dynamic topologies. That means a multi-platform capability is required but not sufficient. In fact, for several reasons, companies are looking for hybrid deployments to run their applications on several platforms simultaneously. Moreover, the topology should support and adjust for new and continuous architecture changes.

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts. Private cloud continues to gain traction with firms realizing the benefits of greater flexibility and dynamic scalability.

Azure Synapse Analytics, still commonly known as Azure Data Warehouse, is Microsoft's cloud data warehouse that processes relational and non-relational data for analytics. As one of the most popular data warehousing tools, Azure lets you generate real-time insights into almost every aspect of your business, from sales to customer service. But how do you get data to Azure in the first place? That's where an Extract, Transform, and Load (ETL) tool proves useful.

According to 451 Research, 96% of enterprises are actively pursuing a hybrid IT strategy. Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. Cloud technologies and respective service providers have evolved solutions to address these challenges.

The Snowflake Data Cloud is a powerful place to work with data because we have made it easy to do difficult things with data, such as breaking down data silos, safely sharing complex data sets, and querying massive amounts of data. As customers move to the Data Cloud, their needs and timelines vary—our goal is to meet every customer where they are on their Data Cloud journey.