The cloud offers many benefits to businesses, enabling a high degree of scalability and flexibility in data warehousing. The current need to efficiently combine data from different, changing data sources and provide easy access to a growing number of decision makers has led many data warehouse teams to move their data warehouse operations to the cloud.
A cloud data warehouse is a database service hosted online by a public cloud service provider. It has the functionality of a local database, but is managed by a third party and can be accessed remotely, moreover, its storage and processing capacity can be scaled down or up instantly if needed.
Differences Between A Traditional And A Cloud Based Data Warehouse
A traditional data warehouse is an architecture for organizing, storing and accessing searchable data in an enterprise data center. A traditional data warehouse is limited in size and computing power and is owned by the organization whose data it stores.
A cloud data warehouse offers flexible storage and computing power, is part of a public cloud data center, is accessible online and is managed by an external operator. The storage and computing power is available on a rental basis only. Physical location is largely irrelevant, except in countries and industries where regulations require data to be stored in the same country as the company’s headquarters.
5 Advantages Of Cloud Data Warehouse
The benefits of cloud data warehouse can be summarized in five points:
Access cloud data warehouse from anywhere, rather than physically accessing databases in data centers. Employees can fix errors from home or out of hours if necessary. The flexible access also means companies can hire skilled workers from anywhere, unlocking previously unavailable talent.
Data centers are expensive to buy and maintain. The buildings in which they are housed need to be properly cooled and protected, specialized staff are required and the databases themselves are extremely expensive. Cloud storage can provide the same service, but businesses only pay for the computing power and storage space they need when they need it. With flexible cloud data warehouse services like Snowflake, computing power and storage can be purchased separately and in different amounts. Businesses only pay for what they really need and can instantly turn off or downgrade features they no longer need.
Cloud service providers complete by offering the most powerful hardware at a fraction of the cost of copying the service on-premises. Updates are automatic, so organizations always have the latest features and there is no downtime when upgrading to the latest version. Some on-premises databases offer better performance, but not at the price and availability of infrastructure as a service (IaaS) offered by cloud providers.
Opening a cloud data warehouse is as easy as creating an account with a provider such as Microsoft Azure, Amazon Redshift, Google BigQuery or Snowflake. The account can be expanded, reduces or even closed again in a snap. Users are informed of the associated costs before the amount of rented storage space is changed. This scalability has given it the name “elastic cloud”.
Storing data in a cloud data warehouse means that companies can switch providers if they change their business strategy. Because they are independent of the database, companies can increase, decrease or completely change their data sets. With metadata and AI driven automation software, businesses can export their entire data infrastructure from the data warehouse to the cloud, migrate it, and allow different teams within the same company to work with the database and hybrid cloud that best suits their needs.
Choose Cloud Data Warehouse Solution
Cost analysis is essential to estimate how much money a company can save by using cloud data warehouse. Different cloud data warehouse service providers have different pricing structures that need to be taken into account. Established providers, such as Amazon and Microsoft, rent nodes and arrays so that a company can use a specific part of the server. This makes the price predictable and stable, but sometimes it is necessary to maintain a particular node.
Snowflake and Google offer a server-less system, which means that the location and number of clusters is not fixed and therefore not relevant. Instead, the customer has to pay exactly for the computing or processing power used. For larger companies, however, it is often difficult to predict the number of users and the volume of processing. Demands can be much higher and cost much more than expected.
Each cloud provider will have its own set of tools to support features such as data management, visualization and predictive analytics, so it is important to consider these specific requirements when choosing a provider.
The use of cloud storage platforms means that organizations can collect even more data from a variety of sources and can scale quickly and flexibly to support an almost unlimited number of users and workloads. By managing the influx of big data and increasing ROI through automation, organizations can manage the influx of big data, automate manual processes and increase ROI from the cloud.