As data storage and analysis continue to migrate from on-premises frameworks to those based in the cloud, the market for cloud storage and data security platforms (DSPs) has expanded. In fact, the global cloud security market is projected to grow from $29.3 billion in 2021 to $106 billion by 2029. This highlights a north star for the future of successful data use: adequately protecting your organization’s sensitive data with holistic cloud storage security measures is imperative.
As cloud storage security becomes a greater imperative for cloud-based organizations, the number of pertinent data security platforms is growing to meet these needs. It’s important that your organization’s data team evaluates their security needs in order to determine which solution will be best for you. In this blog, we’ll examine the growing requirements of cloud storage security and consider some best practices for choosing the right DSP for your organization.
What is Cloud Storage Security?
To keep up with evolving resources and expand their capacity to scale data ecosystems, many modern organizations are migrating data to the cloud. Cloud data platforms like the Snowflake Data Cloud, Databricks Lakehouse, and AWS Redshift provide businesses with the ability to store data within the cloud, which can be scaled alongside business objectives much more effectively than on-premises storage.
When data is moved from on-premises storage to cloud storage, it loses a certain level of passive data security. But while on-premises data is to some degree less accessible to malevolent outside actors, it is by no means immune. And with that, the benefits of this inaccessibility do not outweigh the drawbacks – slow time-to-data, bottlenecked workflows, and lack of scale, to name a few.
To achieve a successful cloud migration, teams must understand the risks of the cloud and take action to proactively protect against them. Cloud storage security methods can include the implementation of:
- Data Access Control: Creating policies that permit or restrict the ability to view, access, and utilize data within a specific system or database.
- Dynamic Data Masking: Modifying or hiding sensitive values in data sets without changing the underlying data.
- Privacy-Enhancing Technologies (PETs): Leveraging methods such as data obfuscation, k-anonymization, and randomized response to protect sensitive data.
Leveraging these types of methods and technologies can help teams to navigate their cloud migration without compromising security.
What are Data Security Platforms?
A data security platform, or DSP, is a software built to combine these various security capabilities into a unified operational system, with the goal of providing a single point of privacy and protection for the sensitive information in a cloud data ecosystem. These capabilities include, but are not limited to:
- Sensitive Data Discovery and Classification
- Data Security and Access Control
- Continuous Data Security Posture Management and Risk Detection
While these features can be found in existing tools, there is a greater shift towards platforms that consolidate them and allow for more end-to-end control over data privacy and security. In a 2022 survey, Gartner found that 75% of organizations are actively pursuing security vendor consolidation, up from 29% in 2020. How should this influence your choice of DSP?
Top 3 Tips for Choosing a Data Security Platform
Due to the dynamic nature of data security at large, as well as the DSP market, choosing a platform that suits your cloud storage security needs might seem like a challenge. Taking these tips into account can help you make the best decision.
Consider Data Security from Square One
This tip is especially relevant if you are just beginning the cloud migration process. Data security, while an essential factor for cloud-based data, is not always baked into the tools and processes from the start. In fact, Gartner notes that “most organizations become aware of [DSP technology] only when they move their data to the cloud and find that their traditional controls no longer suffice.” When this aspect of data use becomes more of an afterthought than a top-line priority, data risk increases. Assessing DSPs early on can cement them into your network and keep data safe from the start.
Platform considerations should also factor into any data ecosystem projects or updates. Whether this includes incorporating new architectures like data mesh or data lakes, evolving tools like artificial intelligence (AI) and large language models (LLMs), or simply adding more system users, it is imperative that your security platform can functionally protect your data wherever it lives and at scale as more users and platforms are added.
Avoid Limiting Your Potential
Data is being created and evolving at an unbridled pace, increasing the difficulty of keeping it safe. The last thing data teams want is a security platform that becomes outdated faster than it can be effective.
Similarly, choosing a platform with a singular, limited focus and capabilities severely limits how applicable your cloud data security measures will be. A platform that only offers data masking or discovery neglects a range of other necessary measures to protect sensitive information.
Instead, only consider data security platforms that maintain the flexibility and efficiency to evolve alongside the data itself. Not only should the platform be able to scale to encompass new data sources and use cases, but it should also offer a wide array of capabilities. Gartner predicts that “at least 70% of data security platform (DSP) expenditure will go to vendors of DSPs with broad (not specialized) capabilities” by 2027. Ultimately, broader is better, and security should not be the only capability driving your DSP adoption.
Examine the Dynamic Field
The data security platform market is in its early stages and still developing. Gartner notes that factors such as “increased attention paid to personal data, the transition of data lakes and AI pipelines to the cloud, the desire to consolidate security architecture and tools, and geopolitical impacts on overall cybersecurity” are contributing to this progressive and changing market.
With this in mind, it’s important to take the time to examine your options and decide which DSP will be the best for your organization’s current and future needs. Data security platforms should be assessed for their range of capabilities, flexible and scalable nature, proven record of success with customers, and integrations with leading cloud data platforms, among other factors. Through this type of holistic examination, you should be able to discern which DSP is best suited for the level of data security you need to maintain.
Maintaining Cloud Storage Security with a Data Security Platform
Ultimately, data security platform choices should be considered as early as possible, measured against similar dynamic and evolving options, and guaranteed to provide a broad spectrum of capabilities rather than a specialized few. With these tips in mind, which DSP is best for your needs?
The Immuta Data Security Platform allows users to enforce and maintain robust cloud security measures from day one. With the necessary capabilities to discover, secure, and detect your organization’s sensitive data, Immuta ensures that only the right people can view the right data at the right times – effectively protecting sensitive information from risk of breach or misuse. Equipped with the broad range of tools required to scale alongside evolving data, Immuta is poised to keep your data safe from the time of implementation forward.
To try creating an Immuta security policy for yourself, give our walkthrough demo a spin.
