Data is today generated in vast quantities, which businesses have to strategically store to ensure it’s easy to access and analyze. While on premise storage is a common option for dealing with this, cloud data warehousing has become an effective alternative.
With cloud data warehousing, businesses store data in the public cloud as part of a managed service. With its inherent structure combined with the scalability of the cloud, it's well-suited for enabling data analytics and future-proofing against the growing data demands of the Internet of Things and AI.
Probing data from across one’s IT estate and connecting it to information from partners and customers can also be done more seamlessly when everything's hosted in the cloud. Better yet, it means you only have to buy as much as you need and can continue to store data in a wide range of formats.
Below, we have summarized four main benefits of cloud data warehousing that every IT leader should consider.
1: Cloud data warehousing meets current and future needs
The cloud is all about elasticity. It lets you expand, or shrink, as fast as necessary – even if the pace is breakneck. You don't need to add storage or compute in preformed 'blocks' where you'll always pay for more than you actually need.
But that doesn't just cover data storage. Today, almost every aspect of your IT needs can be provided by a cloud service.
Software as a service (SaaS) enables a subscription-based purchase model so you only pay for an application as long as you use it. Platform as a service (PaaS) offers the computing environment to develop, test, and launch applications and digital tools on a similar as-needed basis.
And infrastructure as a service (IaaS) is where a provider offers the whole package, from network and storage to data storage and virtualization.
But among all the cloud-heavy technologies today, AI is one of the most prominent. To run AI models effectively, businesses must collect and synthesize cloud service data for deeper insights than the most experienced human data scientist ever could.
2: Data is accommodated and integrated in one place
Storage used to be quite different from analysis, imposing a transport and handling cost between the two. But modern data analytics goes to work on your information where it lives, constantly adjusting in real-time as business conditions change.
Structured data in a cloud data warehouse can be quickly processed, while the environment also allows for new data to be reformatted for meaningful insights on the fly.
All of this means businesses can leverage flexible analysis, no matter how large their data repository is. Independent of department or channel partner, all of this data can be crunched and analyzed in one unified, easy-to-manage space.
3: Cloud data warehousing saves money
Between license fees, hardware, set-up, management, security, and disaster recovery, on-premise or traditional data warehousing costs can add up.
Cloud data warehousing can collapse that cost because it combines many tools in one place and onto one architecture, with each service applied as needed. Businesses don’t have to worry about buying more software or services from third-party vendors who don't necessarily play nice together.
Every tool and technology within the environment has already been thoroughly vetted for interoperability and patched before deployment.
4: Data is secured at rest and in transit
New security protocols and frameworks are emerging all the time, as data in cloud services is increasingly connected to, and exposed to, other information. Keeping your data safe is one of the most important aspects of cloud data warehousing.
Vendor-conducted penetration tests to check for vulnerabilities such as zero-day exploits are a great way to fortify your borders. Another is confidentiality frameworks, which prevent unauthorized access and are usually done through role-based access control, where permissions are assigned to specific roles within a company. Multi-factor authentication (MFA) is a common part of these confidentiality frameworks, where users receive an authentication code sent to a second device, such as their phone, to defend against stolen usernames and passwords.
Integrity measures are another popular area of security, which guarantee data isn't modified or corrupted. These use encryption practices and keys to protect data from unauthorized access.
At the user end, practices like zero trust ensure that all incoming connections or authentication attempts are treated as untrustworthy by default until they have been passed through rigorous security checks to validate their legitimacy. This is the foundation of zero trust network access (ZTNA), which is used for secure remote access to data and applications in the cloud.
While a picture of legitimate requests is maintained, any signal configuration changes or network activity is rigorously monitored, logged, and further interrogated.
