Managing cloud data is an essential responsibility for organizations. A comprehensive cloud data management strategy combines people, processes, and technology to securely and efficiently manage data. If organizations have little or no cost management strategy, the cloud data management challenges will continue to grow.
Cloud providers such as Amazon, Google, Microsoft, and Oracle provide security protection services, including data encryption capabilities, to help reduce security risks. It’s important to note that organizations, rather than cloud providers, bear the responsibility for securing their data. Data management becomes even more complex as organizations spread their data across several cloud providers.
Global data grew 5000% from 2010 to 2020. Who knows how much data the world will have by 2030? Organizations that invest in cloud data management today will be better prepared to handle this exponential data growth.
Are you seeking a career in cloud data management or simply looking to add more knowledge to your technology portfolio? Read on!
Definition of Cloud Data Management
We often draw a comparison between cloud data management and cloud storage. Data storage is a byproduct of data management. Traditional data management methods start with several fundamental principles:
- What is the source of the data?
- What is the role of the data within the organization?
- How long should the data live within the organization?
- Who is handling the data security?
- What is the cost of data management for a specific set of content?
- What is the risk to the organization if the data becomes compromised?
The data management strategy needs to incorporate and embed with the business requirements. Organizations create, distribute, and process data to help serve their business requirements, including meeting customer demands, extending access to business partners, and archiving the content for compliance mandates.
Organizational Risks Because of Poor Data Management
Organizations need a well thought out and defined data management plan to mitigate risks and manage their costs. Early cloud adopters found it difficult to contain their users’ consumption, resulting in unexpected bills from cloud providers. It’s crucial for organizations to have a clear understanding of the data source to avoid unnecessary risks. Another challenging chance is that co-mingling customers internally happens more often than most people think.
Organizations need to track the source data, the purpose, and cost to avoid wasting valuable financial capital. Data owners should continue to be responsible for their data. These data owners should be full of content sources and assign permission based on business needs. However, often data owners from person to person could become compromised.
The importance of data classification is a critical part of traditional data management. Chief information security offers (CISOs) assist data owners by providing security tags and frameworks to help provide guidance. Organizations could classify data supporting the federal government as secret, top secret, or confidential. For non-government entities, they could tag the data as public, private, or archived. Knowing how to organize the data is a significant benefit to the organization.
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Benefits of a Comprehensive Data Management Strategy in the Cloud
Several guiding principles surround the benefits of cloud data management. Storing your data within a single cloud instance helps provide control of the information. Before using cloud storage depositories, organizations often had duplicate copies of the data across several on-premise data centers, inside of backup tapes, or replicated to a cold failure business continuity site. Keeping track of the data became more costly as organizations created more content without a clear retention strategy.
Moving to the cloud and adopting retention policies to govern how long data should stay within the organization is critical to help manage costs and reduce legal liabilities. Retention strategies allow organizations to tag their data to either be automatically removed from all data store depositories or place the content on legal hold. Tags should clearly define these parameters with the data management.
Challenges with Data Management in the Cloud
While data management can bring many benefits to an organization, such as cost management and having a deposition strategy governing data removal, there are also several challenges surrounding data management.
A well-structured data management plan helps save money for organizations. However, developing a data management plan requires an initial investment. Organizations need to spend the initial capital for data management software, hire experienced data engineers to deploy the solution, and need additional IT operations teams to monitor data ingress, consumption, and disposition as part of the cost savings.
Spending on initial and ongoing cloud costs to achieve cost savings is a very delicate balance for organizations. Investing in cloud data integration along with the cloud infrastructure plan is like renting a safe deposit box with rules. What items belong in the safe box and how long the articles should stay is a good analog for cloud data management. Organizations can’t save all their data in one single cloud instance. Part of effective data management is leveraging multi-cloud storage options to reduce costs and mitigate risks by distributing their data.
Does this strategy add complexity and cost? Or does this architecture help reduce cost and risk?
Managing Data Across Multi-Cloud Platforms
Organizations spreading their data across multi-cloud platforms is viewed as possibly a positive strategy move, while others consider it costly and risky.
This strategy is a bit of both!
Why would an organization distribute data across AWS and Microsoft cloud instances? To reduce the risk of data exposure becoming compromised by a cyber attack. Many organizations have become mandated by their board of directors, cybersecurity insurance carriers, and compliance frameworks to maintain data backup. This backup strategy could be part of a business continuity plan (BCP) or simply a replicated copy of data in case the organization needs to failover in order to keep critical production systems operational.
Data management needs provision for this strategy. How organizations distribute data across several cloud instances and what retention policies become implemented is critical. Sending data across many cases without a retention plan or legal hold capability can result in increased storage costs and potential legal fines.
Leveraging separate cloud providers has a very strategic value. In recent years, both Amazon and Microsoft have faced cyber attacks. Fortunately, these tech giants both spend a fortune to protect their cloud assets. Even with these investments, every cloud will suffer a service outage. The time for the cloud provider to recover from a cyber attack becomes measured in milliseconds to a few hours.
Organizations spreading their workloads across different providers do so to meet their business and customer service level agreements (SLAs). Industries such as public utilities, financial services, and healthcare often run under the guise of ‘zero downtime.’ To achieve these business requirements, organizations will update their data management plans to comply with this corporate mandate. Seeking zero downtime requires more than an updated data management plan; organizations must also invest in data management security to help protect their valuable content.
Applying Security Protection to Data in the Cloud
Hackers continue to develop creative ways to steal organizations’ data. These attack vectors lead to data exfiltration from the victim’s cloud storage.
A strong security architecture, protection layer, and ongoing monitoring are critical components of data management. Cloud data management platforms will leverage APIs to communicate with security-specific cloud platforms like cloud-access-security-broker (CASB) and multi-factor authentication solutions to help protect the data.
These cloud security tools help prevent data loss, user impersonation, and denial-of-service attacks against various instances. Another critical piece of cloud data is adopting artificial intelligence (AI) embedded within built-in security tools, such as extended detection and response (XDR), and cloud data migration solutions. AI is also critical in data management, content security, and providing more efficient cloud operations while lowering cloud storage costs.
Knowledge for Today and in the Future
An organization has monitored the early stages of a cybersecurity attack. Their extended detection and response (XDR) platform, powered by AI, picks up the first two stages of the kill chain and begins a secured connection to the cloud data management platform. This connection is created to either shut down access to the instance or execute additional encryption protocols. As a proactive step, data replication in a secured cloud instance could also be considered.
AI will continue to play an essential role in data management, providing more proactive security protection, cloud applications, and mission-critical data.
Software engineers, cybersecurity architects, and data analysts wanting to extend their technology come highly recommended to check out these incredible degree programs and certifications from CIAT.Edu.
These degrees and certifications are ideal for anyone wanting to expand career options into data management within single or multi-cloud environments. Data management is critical for any organization and a solid education in cloud engineering will help open doors for you in the data management field.
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