The need for data to be available and accessible for anyone from anywhere has turned into a major challenge for countless organizations. Cloud computing has brought several benefits to businesses. As a result, many organizations have already migrated to the cloud to better manage their enterprise’s data while keeping it secure. Cloud data management is one service you can use to help you out with this process.
In this article, I’ll explain what cloud data management is and what sets it apart from traditional data management. I’ll also list some use cases, as well as the pros and cons of using cloud data management. Finally, I’ll wrap up by talking about some best practices you can apply and the future of this service.
Firstly, let’s go over what cloud data management actually means.
What Is Cloud Data Management?
Cloud data management is the process of leveraging a cloud-based solution to manage organizational data. A cloud data management service also can help you manage enterprise data irrespective of where it resides.
Moreover, you can deploy it to work with data residing on-premise, in the cloud, or even in multicloud environments. It can help you and your business build and maintain a platform to store, ingest, transform, mine, archive, backup, and secure data. Like any cloud-based service, cloud data management also offers you the flexibility to pay per usage and allows you to easily manage, scale, and save upfront costs.
An effective cloud data management solution has the same capabilities as a traditional on-premise data management service. However, they do differ in some aspects. The section coming up will showcase these differences.
Differences between Cloud Data Management and Traditional Data Management
As previously mentioned, we can list several differences between cloud data management and traditional data management. To this end, I’ve created a simple table for your convenience highlighting these differences. Feel free to use this table as a point of reference should you ever need to.
That said, here are some of the major differences between cloud data management and traditional data management.
|Feature||Cloud Data Management||Traditional Data Management|
|Control||Minimal control over the infrastructure configuration||Maximum control over the infrastructure and access|
|Cost||Requires minimal or no upfront costs||Involves upfront costs to set up the infrastructure and hardware needed|
|Accessibility||Might be an issue as it’s completely dependent on having an active internet connection||Accessible and customizable in the environment it’s deployed|
|Scalability||Easily and highly scalable||Scalability involves the cost of hardware purchase and setup|
|Maintenance||Service provider takes care of the maintenance||You need to maintain the hardware and infrastructure involved|
Now, you should be familiar with how a more modern cloud-based solution fares against a traditional on-premise data management solution. Let’s also take a look at some of cloud data management’s key capabilities and use cases.
Cloud Data Management Key Capabilities and Use Cases
Cloud data management is capable of powering organizations in different domains with several capabilities and use cases. For example, it can simplify the process of data ingestion, processing, and distribution across the world. Furthermore, it can help you with data backup, restoration, and security challenges. Here are some of its key capabilities and use cases:
- Provides consistent data access, support, usage, performance, and security in various data sources
- Integrates with multiple data sources, both on-premise and in the cloud
- Helps you in cloud master data and metadata management by synchronizing different data sources
- Integrates with several other cloud services and downstream applications to automate the data and process flows
- Provides consolidated monitoring, reporting, and visualization dashboards
And there you go! Those are the key capabilities and use cases of this amazing service. However, everything in the world, specifically the IT world, has its advantages and disadvantages. Let’s take a look at this service’s pros and cons next.
Cloud Data Management Pros and Cons
Most pros and cons of this data management mimic those of any traditional cloud service. I’ll go into more detail on these pros and cons right now!
- Security: Modern cloud solutions are often considered more secure than on-premise deployments since they’re backed by timely and automated security updates and patches.
- Accessibility and collaboration: Cloud data management enables employees to access the data they need from wherever they are, resulting in a better collaborative environment.
- Costs: Unlike a traditional data management setup, the cloud counterpart doesn’t involve heavy upfront infrastructure or setup costs.
- Scalability: Like any cloud paradigm, a cloud data management service lets you scale up and down based on your needs and requirements.
- Customization: Cloud data management services can be tailor-made and customized as per your organizational needs.
- Cross-platform compatibility: You can deploy cloud data management to work with data residing on-premise, in the cloud, or with a combination of both.
- Downtime: Every cloud-based service needs an active internet connection, and this can sometimes involve service outages and downtime.
- Limited control: Your service provider owns your data management service and hosts the infrastructure. This also means that you don’t have complete control and visibility of your data.
- Vendor lock-in: One of the most common drawbacks of a cloud service is vendor lock-in. Once you choose a vendor, switching to another is quite an effort and is very costly. Cloud data or service migration also isn’t a trivial process depending on the amount of data and services you need to move. Therefore, choosing the right vendor is very crucial for cloud data management.
- Cost concerns: Although you can mitigate the upfront setup costs, the pay-per-use model can lead to unexpected usage costs if not monitored properly.
So far, I’ve discussed cloud data management’s capabilities, use cases, pros, and cons. However, you can still leverage its benefits in a better way. To this end, I’ll now highlight several best practices you can apply in your organization.
Cloud Data Management Best Practices
Owning and managing data in itself can be very challenging. However, securing data and being able to generate valuable insights is what allows you to gain a competitive edge in the contemporary IT world. For you to be able to do this, you’ll need to have the right practices and strategies in place.
Here are 5 best practices to make the most out of your management service:
1. Define Your Goals and Outline Your Strategy
Before choosing a service vendor or uploading and storing data to the cloud, it’s crucial to note down specific functional and non-functional requirements for your needs. Then, you need to create a detailed data framework, or blueprint, that addresses all these needs. You also need to develop this blueprint before moving to a cloud vendor. Overall, doing this ensures you have a strong foundational basis for your business. Accordingly, it’ll help you choose the right service or vendor.
2. Secure Your Data
Now that you have your data residing in the cloud, it’s your primary responsibility to secure it. Analyze and strategize the data security and governance policies in place and negotiate with your vendor to ensure the security standards meet your requirements. You can also perform data categorization to provide different levels of security based on the nature and confidentiality of the data.
3. Perform Backups
Like every cloud service, cloud data management is also dependent on an active internet connection. It also can include service downtime or interruptions. No business can afford an interruption in business continuity and, more importantly, a data loss. While you can’t control the service interruptions, you can control the data backup cycles. As a result, you’ll ensure any valuable information gets backed up at regular intervals.
4. Control Access to Your Data
You’ll need to regulate, control, and monitor the permissions provided to your employees for accessing the data for security purposes. Implementing user groupings and segregations to provide access rights and permissions can help narrow down the scope of data theft or loss. Finally, apply the principle of least privilege as much as you can to limit access to the most confidential data in your organization.
5. Automate Data Management Tasks
Using automation can help reduce the need for human intervention in several low-level data management tasks such as data integration and backup. This also helps your team focus on more crucial or mission-critical tasks, resulting in efficient use of resources and cost reductions.
We’re coming up to the end of this comprehensive article. Even though you’ve gained a lot of knowledge up to this point, you must still be hungry for more. Before wrapping up, let us briefly touch upon the future of cloud data management in the next section.
The Future of Cloud Data Management
Over 94 percent of global enterprises have already leveraged cloud services for their operations. Moreover, the public cloud service market is expected to reach $623 billion by 2023. These statistics show that cloud computing and cloud-powered services are here to stay. Cloud data management is also capable of providing several businesses with operational advantages. Additionally, it helps bring multiple data sources under one roof. This can, in turn, tackle challenges associated with data silos. Furthermore, cloud data management helps you build a single source of truth for you to tap into and generate valuable business insights when needed.
Clearly then, this paradigm is here to stay. Let’s wrap up.
To conclude, it’s evident that cloud data management can help you streamline and organize your business requirements while allowing you to scale as needed. It can help you save upfront costs, offer customizations, and provide you with several other use cases, as discussed in the previous sections.
In this article, I’ve described what cloud data management is and explained how it differs from traditional data management. I’ve also discussed its major pros and cons, along with some of the best practices for managing your data in the cloud.
Finally, with cloud computing’s high adoption and growth rates, we can expect this service to become more mainstream down the line. This might even allow us to integrate it with several other downstream cloud services.
Do you have more questions on cloud data management? Check out the FAQ and Resources sections below!
What is data management?
Data management is a collective solution used for data gathering, processing, ingestion, storing, transforming, and securing. Primarily, it helps organizations generate valuable data-driven business insights from the data. In turn, it helps optimize performance and operations.
What are some of the major cloud data management service providers?
There are several major cloud data management service providers, such as Amazon, IBM, Microsoft, Google, and SAP. These all offer cloud-based data management services. You also can evaluate all these services against your business requirements to choose one that best suits your needs.
What is a data silo?
A data silo is a disjoint entity or group of data within an organization. It’s often only accessible by limited division, making it disconnected from the rest of the organization. Due to their disjoint nature, data silos can severely impact generating business insights from data.
What industries benefit from cloud data management?
Cloud data management services can affect several industries in the contemporary IT world. Examples include the information technology, automotive, education, and healthcare industries. These, and more, could all benefit from cloud data management services.
What is a multicloud environment?
A multicloud environment is a cloud computing solution that uses more than one cloud service underneath it. Businesses also use multicloud environments to meet various business and operational needs. For instance, using the public cloud to store trivial, publicly available information and using a private cloud to store confidential data is a classic multicloud environment setup.
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