Cloud Analytics

Cloud analytics is a term used to describe cloud-based computing to uncover insight from stored data in private or public clouds. Cloud computing is the fastest-growing segment of the database market, and modern data repositories are almost exclusively cloud-based. Cloud-computing service providers have made it uneconomical to maintain data stores on-premises. Data location is a major factor when deciding where to run data analysis. Cloud storage is virtualized, which allows it to be distributed across multiple physical devices, unencumbered by traditional hardware constraints such as physical volume capacities.

Cloud Analytics Advantages

The traditional database and data warehouse platforms have evolved to embrace the cloud, and new data management technologies have emerged to exploit cloud-based analytics. The cloud offers numerous advantages over on-premises systems, including:

• Elasticity – Cloud computing provides instant scalability to grow and shrink in response to prevailing demand.
• On-Demand Provisioning – Data warehouse instances, including associated software, CPU, and storage, can be provisioned in minutes. Traditional IT systems can take weeks to purchase, configure and deploy servers.
• Subscription Pricing – Only pay for the cloud resources being used. Instances can be stopped, and storage can be deallocated when not needed. On-premise servers and storage arrays cost money even when not actively used. On-premise servers must be sized to anticipate processing peaks and a buffer for growth.
• Cloud Resources – Can be easily mirrored to multiple cloud regions for higher performance availability.
• Block Storage – Decouples compute and storage resources so either can be scaled independently of the other.
• Lower Cost – Cloud providers pass on the economies of scale they enjoy to their customers, lowering their infrastructure costs.
• Manageability – When a business deploys in the cloud, they devolve high IT administration costs because cloud providers take care of any required device maintenance and software patching.

Why Run Analytics in the Cloud?

One of the most significant benefits of data analysis in the cloud is that there is no client-side application to maintain. A truly cloud-native analytics solution includes the ability to create and modify SQL statements in a web browser. Query results and visualizations can be viewed in the browser with the ability to download to local spreadsheets or reports if needed.

Having the source data organized for easy analysis and the tools to analyze it in one place makes life easier for both users and IT.

Analyzing data in the cloud it resides in has immense value because moving data between clouds wastes time and often incurs egress charges.

All the major Business Intelligence (BI) tools can connect to cloud data sources using standard APIs. Applications can similarly be connected to cloud-based data.

Distributed Cloud Analytics

Multinational businesses have employees around the globe who have a local focus. These users need to be able to analyze business unit performance at both the country and regional levels. Public cloud providers have regional data centers that can host local data and provide compute resources to analyze that data. This gives regions some autonomy from HQ, and the local users benefit from better query performance thanks to low-latency network connections to their data.

Central HQ needs a consolidated picture of global company performance with the ability to drill down for detailed regional analysis. A modern analytics solution such as the Actian Data Platform supports distributed queries across multiple instances to provide up-to-date results. In this case, subqueries can be executed on regional instances and only transmit results to the HQ instance for aggregation. This avoids the need to keep multiple copies of data.

Actian and the Data Intelligence Platform

Actian Data Intelligence Platform is purpose-built to help organizations unify, manage, and understand their data across hybrid environments. It brings together metadata management, governance, lineage, quality monitoring, and automation in a single platform. This enables teams to see where data comes from, how it’s used, and whether it meets internal and external requirements.

Through its centralized interface, Actian supports real-time insight into data structures and flows, making it easier to apply policies, resolve issues, and collaborate across departments. The platform also helps connect data to business context, enabling teams to use data more effectively and responsibly. Actian’s platform is designed to scale with evolving data ecosystems, supporting consistent, intelligent, and secure data use across the enterprise. Request your personalized demo.