Cloud Data Warehouse

Cloud Data Innovation

A tech professional woman analyzes cloud data innovation on a laptop in a server room

Cloud computing has been a positive development in the IT landscape as it has become the foundation for new capabilities that have forever changed how organizations create and deliver applications.

Why Cloud Innovation is Important

The notion of using other people’s computers is not new. Many early computing systems were shared using time-sharing services simply because few businesses could afford such multi-million-dollar systems. Over time, less expensive mainframes, midrange, and personal computers became affordable for most companies. With the advent of the internet, anyone with a web browser could gain access to server applications.

Similarly, cloud computing has become an integral part of modern IT infrastructure for businesses of all sizes. The cloud allows companies to access computing resources on-demand from a cloud provider for greater scalability, agility, and performance. Rather than building and operating expensive data centers, businesses can focus on more important aspects of the business, such as creating new innovative services for their customers and expanding into new markets.

Key Innovations

The following are some of the more significant innovations that have made cloud computing so pervasive.

On-Demand Availability

Before the availability of cloud computing, getting access to a new IT service could take weeks. Organizations need to procure, configure, and provision servers. Cloud offers self-service capabilities that allow users to subscribe to a service, train themselves, and begin using it, often within hours, without waiting for IT.

Subscription Pricing with Metering

Providers meter cloud services so they know exactly how much resources you consume. This is calculated and charged monthly, just like a utility bill. Because cloud platform providers buy such volumes, they can afford to offer customers IT infrastructure and applications at commodity-level prices, making the purchase and running their own IT hardware and software uneconomical.

Elastic Scalability

Factors such as physical rack space, power capacity, cooling capacity, and network bandwidth can constrain on-premises data centers. Cloud computing data centers are generally over-provisioned to the level that they can offer more capacity than any business might need on demand. This ability to provide capacity to match unpredictable user demand spikes is very compelling to any business that depends on customers who expect a highly responsive service.


Early cloud technology only hosted standard apps on dedicated servers. Multi-tenancy allows multiple organizations to share a single database instance with assured security. This dramatically reduces service costs for the provider, which it passes on to the customer.

Application Programming Interfaces (APIs)

Giving customers and developers the same application interfaces that are available when they run on-premises systems has made cloud migrations easy and transparent. Whether accessing a shared file or calling another application, users are unaware whether the server is local or in the cloud.

Serverless Computing

Cloud providers offer infrastructure at increasingly higher levels of abstraction. With serverless computing, the application runs without worrying the developer about the infrastructure it uses. AWS Lambda, Google Cloud Functions, Microsoft Azure Functions, and IBM Cloud Code Engine are serverless computing services.

Separation of Compute and Storage

Decoupling computational resources from data storage resources allows resources to scale independently, helps prevent cascading failures and enhances overall system reliability and availability. Separation of compute and storage can optimize resource allocation and reduce costs with the flexibility to vary the ratio of CPU to storage to meet application demands.

Big Data in the Cloud

Big data refers to extremely large and complex datasets that traditional data processing techniques cannot easily process. Hadoop was an early framework for processing and storing big data. While still valuable for specific use cases, Hadoop can be complex to set up and manage. Newer technologies such as Apache Spark, Amazon EMR, Kafka, and NoSQL databases with distributed data storage offer improved ease of use, performance, and scalability, making them attractive choices for certain situations.

Cloud Databases

The database market has evolved to embrace the cloud, making it the fastest-growing segment. The cloud makes high availability easier by mirroring writes to multiple devices. On-premises volume size restrictions go away. Cloud database servers can scale to match query and user volume demands and scale back to save execution costs.

Secure Access

The combination of Secure Sockets Layer (SSL) and HyperText Markup Language (HTML) provides secure browser-based access to cloud applications. Web applications have matured to offer the same usability we have come to expect from fat clients but with less maintenance effort. Features such as drag and drop, radio buttons, and document previews behave just like their client-server counterparts. Organizations can secure sensitive data in specialist services such as the government cloud for enhanced security and compliance.

Responsive Design

Whether you are accessing a cloud application from a PC, tablet, or mobile device, the user interface adapts to that device’s screen dimensions and input device without extensive coding thanks to Cascading Style Sheets (CSS3) and HTML5 advancements.

Actian and Cloud Data Innovation

The Actian Data Platform provides one place for a business to maintain data management projects. The Actian Data Platform can host data warehouse instances on public clouds or on-premises. Data integration technology connects to hundreds of sources and transforms data to become analysis ready. Register for a free trial of the Actian Data Platform here.