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Cloud data management model

How an organization manages cloud data depends on who needs to access it, how often, where and for what purpose.

When planning governance policies and processes, organizations must consider the needs of the teams that protect and use the data, as well as the needs of the teams that pay the bills.

Security, business, and finance teams all play a role, and everyone’s role includes being a good data steward—it’s no longer just IT’s responsibility.

Jake Reichert, vice president of engineering at Yotascale, said organizations should build automated and continuous data discovery processes, including remediation of any provision of personal data based on company policies and consumer preferences.

“If you use multiple cloud providers, invest in a third-party cloud cost management solution for a unified view of costs and a more granular view broken down by business unit, team or product line ,”He says.

When an organization knows what or who is driving cloud costs, it can collaborate with these consumers on usage, optimization, and governance strategies to ensure business value from cloud workloads.

Karl Martin, Chief Technology Officer at Integrated.ai, added that a key step is to understand and plan the expected ways of extracting value from data assets before implementing new data management initiatives.

“Historically, investments in common data management tools, such as data lakes, have been made without a full understanding of how to extract value,” he said.

This strategy often assumes that it is “find later”, which produces disappointing results for organizations that have difficulty mapping potentially large data assets to business problems.

“In some cases, data management systems that do not take into account the needs of modern machine learning systems will be at the center of cre providing active experimentation for data scientists and line-of-business owners,” explains Martin road.

Security plays a key role in data management

Martin says Data security (and closely related data governance) is a necessary layer of the entire data management roadmap.

It ensures that data access – who, what and how – complies with all relevant policies and contracts.

“Ultimately, it’s a key enabler in ensuring that data systems are trustworthy and accessible only to authorized people and systems,” Martin said.

Without proper investment in data security (including frequently updated expertise and tools), data management has no “teeth” and presents significant risks to the organization.

Reichert agrees that everyone’s level of security is a critical component of cloud data management.

“Data breaches, whether accidental or intentional, can result in serious legal, financial and brand damage,” he said. “But to get the most ROI from your data plan, you have to strike a balance between security and availability, and that’s best achieved at the data security level.”

He added that lucky The thing is, there are plenty of excellent security tools on the market to help manage data-level security, from encryption and masking to role-based access control.

Hank Schless, senior manager of security solutions at secure service edge (SSE) provider Lookout, says organizations need to ensure their security policies take into account data that has become more complex as everyone is based on applications in the cloud, with different data types from different locations and devices.

“It used to be those data confined to the four walls of an office building or wherever the local servers were,” he said. “We can now access sensitive data from anywhere via the cloud or web-enabled applications.”

Schless explained that security and data management teams should be working in stride to ensure data doesn’t move to anywhere existing security teams cannot protect.

In addition, acknowledging how employees access and process data is critical to any modern security strategy.

“Organizations are looking to integrate solutions that monitor and protect data to prevent security breaches that could lead to data breaches,” he said. “Combining data security and data management best practices will also help organizations ensure their alignment with complex data compliance and privacy laws.”

As data management models evolve, multi-stakeholder

Vectra’s Aaron Turner, CTO of SaaS Protect, said business process owner, partner Both regulatory and safety leaders should work together on a coordinated strategy.

“Business leaders are generally pushing to do faster, compliance leaders are trying to keep up with data protection requirements, and security leaders are holding on to them as new technologies are introduced nails,” he said.

Putting all these challenges together, regular data protection audits and penetration testing are now more necessary than ever.

This means that for some stakeholders, duties that may have been part-time jobs will now not only become full-time jobs, but may s The pace of change caused by data migration to the cloud.

Integrate.ai’s Martin adds that there are many roles involved in planning cloud data management investments, spanning strategy, policy, IT implementation and IT operations.

He said that historically, IT and privacy will be the main stakeholders, focusing primarily on implementation and operations, while ensuring governance requirements are met.

However, as the industry matures, there is a growing focus on better predicting ROI and implementing data value extraction.

Martin added that in organizations where machine learning is most advanced, technology is increasingly used as a means to extract value from data, so there is an opportunity to predict and measure business impact in a more accurate way .

“Think of cloud data management as just an IT cost center, but understand and predict the value generation for the associated line of business,” he said.

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