Data Management in the Cloud

Data Management in The Cloud: The Answer to Your Data Storage Needs

Revelate

Table Of Contents

Data management serves as one of the most challenging tasks for most organizations. In fact, companies are at risk of losing millions of dollars each year, without proper data management systems in place.

Past methods of data management that relied on on-premesis systems and manual processes are no longer standard and necessary to take advantage of the business opportunities that organizational data offers. These days, cloud-based data management systems are secure, effective, and efficient ways to organize data so all stakeholders can reap the benefits from it.

This guide talks about data management in cloud systems and their various features. It also gives you a rundown of its benefits and risks and why platforms like Snowflake and Databricks can be your all-in-one solution in guaranteeing proper data management for all.

What is Cloud Data Management?

Cloud data management is a way to manage and store data across various cloud platforms. This can be achieved either with or without on-premise storage. If it’s done offsite, the data center is overseen and owned by a data manager specializing in public cloud infrastructure.

With cloud data management, data sharing is also possible, regardless of whether clouds are private or public. Despite the ability to easily share data, stored data in the cloud should follow a set of rules to ensure data security and integrity. That way, businesses ensure the privacy and security of any information shared throughout the system.

Cloud data management provides businesses with the following benefits:

  • Automated backup processes
  • Convenient from any location
  • Disaster recovery
  • Long-term archiving
  • Backup
  • Professional support

They can also support managing data more efficiently by modifying the storage system to an organization’s exact needs.

Cloud Data Management vs. Cloud Storage

Cloud data management or cloud computing significantly differs from cloud storage. A few of the key differences are summarized in the table below.

Cloud Data Management Cloud Storage
Used to link together multiple cloud storage systems Mainly for storage and keeping data secure
Removes the need for added security Removes the need to purchase your own storage infrastructure
Mainly for businesses Can be used for business or personal purposes
Ensures safe, secure data sharing and centralized data management Ensure all data are stored in one place to prevent confusion and breaches

Cloud storage is essentially a type of cloud computing that allows you to upload data to a cloud computing provider. That cloud can then be accessed using an internet connection or through a private network connection.

Cloud storage allows businesses to securely maintain their data without having to worry about management, storage capacity, servers, and infrastructure. All those functions are handled by the cloud storage provider instead.

One of the advantages of cloud storage is that it tends to have unlimited space. As a result, it’s highly scalable and can keep up with business growth.

On the other hand, cloud data management is useful for bringing together multiple cloud data platforms so that you can effectively handle data. It unites separate cloud storage solutions into one coherent and functional system.

Additionally, cloud data management provides proper security and access tools. That way, you can safely link these storage systems without putting important business or customer data at risk.

Cloud Data Lakes vs. On-Premesis Data Lakes

In the past, low-cost data repositories were handled by on-premesis data lakes. While these systems were intended to be scalable, the sheer volume of data quickly caused the growth of these systems to be unsustainable, mainly due to issues surrounding performance, data governance, and being overall high maintenance. With the security and fidelity of cloud-based storage pretty much guaranteed by providers such as Google, Microsoft, and Amazon AWS, cloud data lakes quickly rose as the obvious modern solution.

Cloud Data Lakes On-Premesis Data Lakes
Infinitely scalable with the ability to dynamically change computing clusters as needed, and the ability to support a nearly-unlimited number of users Scalable, but at great cost to the organization in terms of resources and maintenance, making it an unsustainable solution
SaaS providers manage data governance, security, provisioning, backups, and more to eliminate the need for an individual organization to manage their own maintenance Management and maintenance of the system is the responsibility of the organization itself
Can handle a large amount of structured, semi-structured, and unstructured data System limitations, cost, as well as bandwidth constraints limit the amount of storage available
Cloud-based data lake tools allow more efficient pipeline building, and most solutions have pre-integrated data pipelines ready to go Setting up effective data pipelines is extremely complex on both the hardware and software side

Data lakes can also accomplish the following additional tasks:

  1. Store data in full fidelity
  2. Process real-time and batch-mode data
  3. Perform data analytics through any third-party data or application

Regardless of what cloud data lake provider you use, Revelate can extract data from it and transform it according to your fufillment needs. Data sets can be accessed on-demand via your customized web store, eliminating data silos and making it easy for any stakeholder to access the data that they need.

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Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

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Data Modernization

Cloud data management is actually a part of a broader system: data modernization. It allows the movement of data across legacy and modern databases.

Data modernization is essentially the process of transferring data out of siloed databases and into modern cloud-based systems. 

These modern data infrastructures, such as clouds, lakes, and warehouses, allow businesses more insights into the data that they already have. As a result, they can more efficiently handle their data to benefit their businesses.

Another thing to note is that because of its enhanced efficiency, data modernization has a lower cost than other data management technologies in the past.

It also provides increased security and data privacy, helping better protect sensitive information.

Best Practices for Data Management in the Cloud

Best Practices for Data Management in the Cloud

Good data management in the cloud involves compliance, performance, monitoring, and security, among other things. 

By having these types of best practices in place, businesses can properly manage their data and avoid serious issues such as data breaches.

Let’s take a closer look at a few best practices for data management in the cloud.

Security

Security breaches are up 68% since 2021, making proper security a key part of good data management in the cloud.

A few things that businesses should be implementing in order to enhance data security include:

  1. Practicing safe data management access
  2. Compliance enforcement
  3. Utilizing best use policies to reduce security breaches and abuse risks

On top of this, most cloud data management systems actually offer additional privacy and protection settings. These settings allow users to:

  • Automate and speed up classification and discovery of sensitive data
  • Make privacy policies operational
  • Support rules on data access
  • Define clear ownership identities
  • Ensure data protection
  • Analyze and identify possible data risk exposure in various storage locations

Another important part of security in cloud data management is to backup your data. This ensures you don’t lose any essential information when breaches or errors occur. Many SaaS systems will actually run these backups automatically, but it still pays to double-check.

Governance & Compliance

Cloud data management should clearly define the policies for performing activities involved in quality, data collection, access, protection, and retention. This is generally referred to as data governance. Without data governance, you are increasing possible risks that could decrease business value.

Additionally, data governance contributes to staying compliant with current regulations. A few key parts of good data governance include implementing:

  • Privacy and protection
  • Ownership and accountability
  • Embedded controls
  • Consent management
  • Audit and reporting
  • Monitoring and analysis

These practices can not only keep your data organized but can ensure that you’re adhering to regulations for managing data and private information.

Performance Monitoring

Like any process or tool, cloud data management needs efficient performance monitoring. Monitoring helps users identify whether the current system works. Moreover, it enables you to analyze the current cloud storage and available networks.

Performance monitoring also ensures you’re taking advantage of all the benefits of cloud data management. By analyzing your data, you can generate ways to improve the cloud’s application in keeping your business information secured.

Cost Management

One of the primary reasons most individuals opt to use the cloud for storage and data management is the reduced cost. However, some businesses had increased operational costs or incurred unnecessary costs because of utilizing clouds for managing their information.

To ensure you’re using the best strategies for your cloud data management, managing your costs is also key. This means setting budgets and running an analysis of where costs are being effectively used and where they aren’t.

In some cases, you can scale back your cloud’s capacity or otherwise optimize it so that you aren’t spending over budget.

Automation

Automation is important, especially for securing your data protection strategies. It speeds up tasks and processes, especially when dealing with large quantities of data.

These tasks range from monitoring to reporting, testing, and integration. Automation can help make your IT team focus on fostering innovation and managing more critical tasks, rather than on low-level tasks that shouldn’t be taking as much time.

Several automation tools can perform complicated tasks and reduce human errors and management costs.

The Pros and Cons of Data Management on Cloud

As with any other process you implement, cloud data management has its own benefits and challenges.

Knowing both of these is the key to successful data management on the cloud. Let’s take a closer look at both the benefits and difficulties of using cloud data management.

Challenges

Most challenges you experience with cloud data management are the same drawbacks of traditional cloud technologies.

The four primary challenges include:

  1. Data Egress Fees and Cost
  2. Data Integrity
  3. Security
  4. Downtime

Let’s go over these in a bit more depth.

Data Egress Fees and Cost

While most cloud providers allow you to input data for free, retrieving them can incur charges. The fees you pay are called data egress fees. Cloud providers charge this fee whenever data is transferred from one premise to another.

Because of the high egress charges, most organizations prefer to keep data in cloud premises rather than regularly retrieving it. However, this can incur large storage costs, resulting in the same issue of high additional fees.

Data Integrity

Cloud data management also needs integrity assurance, like most on-premises data management platforms. Issues involving integrity include possible duplication and conflicts in taking contradictory records.

Furthermore, these systems can also experience errors in ensuring data accuracy when its integrity is not guaranteed. As a result, it’s possible to have inaccurate or incomplete data, which can later affect your processes.

Security

Security risk is also a drawback of cloud data management. It’s one of the main reasons why cloud service providers are very strict with their data access policies.

To overcome this challenge, you must ensure that the service provider you choose guarantees only authorized users have access to the cloud. This way, you can limit third-party access to sensitive information and ensure data only gets into the right hands.

Possible Downtime

With cloud data management, everything happens using internet connectivity. When there’s downtime on the network, you’re unable to accomplish daily goals and tasks.

As a result, down networks, disrupted connectivity, power loss, and service maintenance can all be challenges of data cloud management.

Benefits

The advantages of cloud data management are much similar to the benefits of conventional cloud services. However, there are a few added advantages to be aware of.

The key benefits that cloud data management can provide include:

  • Scalability and tiered pricing
  • Ease of access
  • Automated backups
  • Elimination of duplicate data
  • Sustainability

Let’s go over these benefits in more detail.

Scalability and Tiered Pricing

It’s important that on-premises data storage is closely monitored to ensure space availability all the time. When the storage runs out of space, organizations should purchase extra to fit all their needs.

With cloud data management, however, organizations have unlimited cloud storage that is always available. This makes it easy to increase the scope of data a business manages as it grows.

Because cloud data management is highly scalable, companies can scale the available storage according to the required space. When the project is not huge, companies can scale down the available cloud storage to avoid paying unwanted fees.

Of course, there are generally tiered pricing packages that oversee how much data an organization can store. Still, these solutions tend to be cheaper than on-premises storage costs and allow for greater functionality and storage.

Access Anywhere

Cloud data management allows individuals to access data wherever and whenever. It also allows collaborative tasks because employees can work together and share their insights on a single dataset.

As a result, it becomes easier to share information across organizations. This ease of access also makes project collaboration much more convenient.

Automated Backups

Cloud storage automatically backs up data, allowing companies to focus on other business-related things. Having automatic backups also guarantees your data are kept safe inside the cloud.

Moreover, automatic backups ensure faster disaster recovery after emergency breaches and errors. This helps in preventing ransomware attacks.

Helps Eliminate Duplicate Data

Cloud data management centralizes all data, guaranteeing organizations work on a single data set. The main advantage of having centralized data is it reduces the risks of duplicating data and inconsistencies, which could negatively affect business operations.

Sustainability

If you’re an advocate of environmentalism, cloud data management is something you should be considering. Cloud data management decreases your organization’s environmental impact, reducing your carbon footprint.

Because everything is digital with cloud management, you don’t have to worry about paper waste or other byproducts of data storage.

How Revelate Works with Data Management in the Cloud

How Revelate Works with Data Management in the Cloud

Revelate eliminates barriers that prevent companies and organizations from fully utilizing their data. It does this by facilitating a streamlined data fulfillment process that connects organizational data to the people who need it, without barriers. When combined with a cloud-based data management solution, the efficiency and effectiveness of organizational data for every workflow, use case, and process increased exponentially.

Platform Agnostic

Many cloud data management providers strongly encourage users to stay within their ecosystem for every aspect of data fulfillment. The problem is, not every customer will be using the same ecosystem, with can severely limit the reach and overall potential of data sets. Even internally, large organizations like Governments, healthcare organizations, and corporations with various child companies and partners are going to have their own processes and preferences when it comes to their data ecosystems.

Since Revelate is platform agnostic, it can extract data from any source, prepare it according to a customer’s specifications, and fulfill a data order on a web store, all on-demand. Processed data can be sent to a customized Revelate data web store or to another platform such as Databricks or Snowflake for fulfillment. This truly provides a complete data democratization experience, since it unifies data fulfillment regardless of platform.

Simplify Data Fulfillment with Revelate

Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

Get Started

Top-Notch Data Analytics

Revelate utilizes advanced cloud technologies and provides analytics on web store sales. The result is that businesses are equipped with additional insights that let them work on and improve their data product offerings.

Additionally, with these analytics, businesses can better interpret their sales to see what’s driving revenue and how to maximize that. This allows businesses to make use of, organize, and better understand key data that’s already available to them.

All-in-One Platform for Data Monetization and Achieving Unity

Revelate offers the best convenience you’re looking for in a data fulfillment platform. Using automated processes, data orders are fulfilled on-demand regardless of the source. This means a couple of things with regards to monetization and unity of data:

  1. It’s easier to monetize data. Because Revelate is platform agnostic and provides a fully-customizable web store, data can be extracted from any source, automatically prepared, and placed on your web store for your customers to consume. Most data marketplaces place limitations on how data products are displayed for consistency reasons, meaning that data products are limited in the depth and scope of displayed information. This can lead to fewer downloads if customers are not able to understand the contents of your data set based on what’s displayed on the marketplace. Plus, most marketplaces limit access to members only. With Revelate, you can create one data web store with public, private, and hybrid access to expand the reach of your data products, while still retaining full control over access levels.
  2. Provide access to data regardless of ecosystem. As we mentioned before, customers, partners, and companies will all have different ways of storing and managing their data. Because Revelate can access data from any system, it democratizes data access in a way that closed systems cannot.

Furthermore, Revelate does not assume ownership of your data so you can guarantee the safety and security of your datasets.

Conclusion

Cloud data management offers security, versatility, and ideal data management assistance. Through this data management method, you’re guaranteed each team member has access to data they need whenever and wherever they need them.

Data governance, security, performance monitoring, automation, and cost management are the key aspects you should look into when employing the best practices for cloud data management.

Upscaling your data management can be the best thing you do for your business. If you’re looking for a reputable platform, check out Revelate’s Databricks Integration. Its all-in-one data handling solution might just be what you need to enhance your team’s collaboration and data sharing.

Simplify Data Fulfillment with Revelate

Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

Get Started