3 Predictions for Data Security in 2022

While the pandemic’s effects are still being felt, organizations have had a chance to reflect on and adapt to the changes it precipitated, and address how to best move forward. Throughout 2021, we saw shifts in data security take root as digital transformation accelerated faster than anyone predicted.

In the closing weeks of 2021, we’re taking a look back at the major developments that shaped data access control this year, and examining trends that will impact organizations in 2022 and beyond. We’ve glimpsed the future, and we think 2022 is going to be the year of compliance as organizations make massive investments to improve security and privacy.

Looking Back on 2021

To keep up with an increasingly digital world, companies continued to emphasize data collection, usage, and analysis as a strategic objective. In order to successfully manage data-driven initiatives, the role of Chief Data Officer (CDO) went mainstream. A joint survey by Immuta and 451 Research found that 60% of respondents report having a CDO at their organization, and the rising popularity of this role is correlated with businesses’ data maturity.

As data use continues to evolve rapidly, so too have the cloud data architectures. During 2021, we saw data platform architectures like data mesh rise in prevalence. Moving away from monolithic storage models like data lakes and warehouses, the data mesh architecture decentralizes storage to create more autonomy and fewer bottlenecks in an organization’s data analytics processes. Innovations like data mesh have continued to reinforce data’s versatility, and exhibit how imperative data accessibility is in business today.

This past year, we also saw renewed interest in data security worldwide. Many high-profile data breaches, such as those experienced by Twitch, Facebook, and Colonial Pipeline, impacted millions of consumers and made international news. The United States signed on to the Paris Call for Trust and Security in Cyberspace this year, joining more than 80 other countries and a wealth of tech companies in the international pursuit of data privacy and protection. Coupled with new security frameworks like Zero Trust architectures, the focus on data security has been galvanized in 2021 and will certainly extend into the future.

Looking Forward to 2022

2021 showed us that cloud data use is anything but static. Understanding the trends of the past 12 months, we can now look towards what is yet to come. Here are Immuta’s top three predictions for data security in 2022:

1. Cloud adoption will accelerate.

Widespread migration to the cloud kicked into high gear in 2020 as organizations were forced to adapt to the pandemic’s impacts. It’s now becoming even more relevant as organizations recognize the wide-ranging benefits of adopting cloud-based compute and storage models. Whether seen in cost savings or optimized performance, the faster time-to-value and time-to-production associated with the cloud are nearly impossible to pass up.

While last year’s 2021 Immuta Data Engineering Survey found that 71% of respondents expected their businesses to be “entirely” or “primarily” cloud-based within 24 months, that number has since increased substantially. Our 2022 State of Data Engineering report found that 81% of respondents now expect to be fully or primarily cloud-based before 2025. Platforms like Postgres, Snowflake, Databricks, and Amazon Athena are growing in popularity with companies looking to shift to the cloud or expand within it.

With cloud analytics becoming the standard for businesses, it is critical that cloud data platforms optimize data utility. Whether based in a single- or multi-cloud model, data teams need to guarantee that their data is secure and up to regulatory standards. Governance also must be balanced with accessibility, so that one does not impinge upon the other. Incorporating an automated data access control model into your cloud platform can provide this balance.

2. Data quality will be more important than ever.

The quantity of a company’s data doesn’t matter much if it’s consistently low-quality. With a wealth of contemporary services and products relying on data to succeed, inaccurate or low quality data can greatly inhibit data-driven initiatives. As analytics and machine learning applications rapidly expand, usable data is paramount to continued efficacy.

Our 2022 State of Data Engineering survey found that Data Quality and Validation are the most prevalent challenges for data teams. Additionally, more than a quarter of respondents (27%) were unsure if their organization is using any data quality solution at all. Even if the need for quality assurance is high among data practitioners, the lack of high-level response can create an enormously unproductive disconnect.

As data usage and reliance expands, this problem has the potential to aggravate workflows. More complex platforms and architectures, coupled with exponentially-increasing data sources, can create an ecosystem with immense risk for low quality data. That is why adopting systematic data quality solutions will be integral as analytics continue to evolve. Preemptive solutions, ranging from metadata management and AI/ML auditing to attribute-based data access control, can work to guarantee that high quality data is reaching the necessary people, without risk of unmanageable data copies or modifications.

3. Privacy engineering will be essential to regulatory compliance.

As data use continues to expand, so are the number of privacy rules and regulations. Gartner’s 2021 Hype Cycle for Privacy estimates that 75% of the world’s population will have its personal information covered under privacy regulations by the year 2024. These regulatory data protection measures can be both legal (like GDPR and HIPAA) or internal to a company.

The more rules that apply to an organization’s data use, the more attention must be paid to proper regulatory compliance. That is why privacy-enhancing technologies (PETs) are becoming more mainstream in businesses’ data platforms. Some of these PETs, such as sensitive data discovery and classification, and dynamic data masking, are widely utilized. Other newer privacy measures, like differential privacy, are becoming equally integral to achieving compliance.

It is becoming more effective to build privacy engineering methods into data pipelines from the start, rather than treating them as an afterthought. Regulations aren’t going anywhere, and companies will need to focus more on proactively meeting these internal and external requirements. Utilizing software that can layer into existing cloud networks and use PETs to meet regulatory standards can alleviate risk, burdens on data practitioners, and unnecessary costs.

How to meet these needs in 2022:

Taken in aggregate, the needs of cloud migration, data quality assurance, and regulatory compliance can make data use in 2022 and beyond seem daunting. However, solutions to these pertinent demands might be easier than you think.

With a universal cloud data access control platform like Immuta, organizations can supplement their cloud infrastructure and meet these needs with universal cloud compatibility, dynamic access controls, and a range of PETs. As cloud adoption accelerates, data quality rises in necessity, and regulatory requirements become more stringent, scalable and dynamic data access control will be a business imperative.

Immuta’s SaaS deployment provides users with a scalable, flexible, and secure platform that can facilitate a compliant and effective migration to the cloud. To learn more about how Immuta can help you meet 2022’s challenges head-on, request a free trial.


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