Alteryx Special Edition Cloud Analytics Automation

In the not-too-distant past, most data storage and compute operations took place exclusively in on-premises data centers, which limited scale and was often prohibitively expensive. As the amount of data being generated continued to grow at an exponential rate, it was becoming increasingly challenging for traditional data warehouses to keep up with business requirements and scale in a timely and cost-effective manner.
With the cloud-computing era, most of these constraints became a thing of the past. The cloud enables large-scale processing of data at lower costs, increased scale, and reduced time. Today, the cloud is the de facto solution for data processing and performing advanced analytics to gain business insights.
Traditional data warehouses have increasingly moved from onpremises to the cloud, leading to the proliferation of cloud data warehouses such as Google BigQuery, Amazon Redshift, Snowflake, and Databricks. These repositories can consolidate data from multiple sources; store the data securely; maintain a high level of consistency, quality, and accuracy; and transform the way data is delivered and consumed.