BrandPosts are written and edited by members of our sponsor community. BrandPosts create an opportunity for an individual sponsor to provide insight and commentary from their point-of-view directly to our audience. The editorial team does not participate in the writing or editing of BrandPosts.
Modernizing and future-proofing your analytics
Executive-level commitment to a broad data governance strategy is gaining momentum in order to balance technology, people, and processes. In a recent Gartner survey, 78% of CFOs said they will increase or maintain enterprise digital investments. And a Gartner forecast states worldwide IT spending will grow 3% in 2022.
The counterbalance to this positive trend comes from NewVantage Partners’ Data and AI Leadership Executive Survey 2022, which states only 26% of respondents claim to have reached their data goals. The gap between data winners and stragglers is widening.
One look at the Andreessen-Horowitz framework for the modern data infrastructure and you see data ecosystem complexity is becoming a nightmare to manage. The ability to properly secure this new smorgasbord of data platform choices increases the management challenge.
Andreessen-Horowitz framework for the modern data infrastructure
Until recently, data management and analysis was almost solely an IT function. Today, the business ranks are filled with similar skills with data stewards, data analysts, and data scientists tasked to build a data security governance platform. Meanwhile, CISOs, CIOs, and CDOs are thinking about compliance requirements and implementation. And IT has seen dwindling resources to cater to data consumers. While there are many positives regarding the expansion of data-related roles, it has also meant dwindling IT resources directly dedicated to data consumers, despite IT being tasked with servicing a growing data landscape.
On-premises technologies have moved to the cloud, often in an à la carte, buy-as-you-go style, without significant forward-looking strategy. In addition, a stream of new regulations demands new processes to regulate and assure the responsible discovery, access, and use of data. Add to this the federation of our data expertise into the business functions, and organizations now require a scalable approach to data governance processes.
The growing cost of getting it wrong
While many proof points exist for the value of data and the positive impact, the cost of doing nothing or getting it wrong has gone somewhat unnoticed. Key considerations include:
Regulatory fines, such as GDPR, are becoming real with companies such as Amazon and WhatsApp reporting multi-hundred-thousand-dollar fines.
Analyst, data engineer, and data scientist productivity remains a major challenge as they continue to report 80% of their time is spent on finding and getting access to the right data, as well as cleaning that data.
The intangible cost of delayed business decisions because the projects are on hold or severely impacted and delayed.
Loss of consumer trust once confidence is broken due to mishandling of data, causing lasting damages to a company’s brand as well as severe financial repercussions.
Modernizing your data security governance thinking
Modernization starts with thinking differently about the approach to people, processes, and technology.
Modernizing data security governance technology: Security and data governance need to exist across every part of the data lifecycle. Maintaining that security posture on a point-by-point basis is simply not viable. A broad-based data security platform that will bring you a centralized data security control plane across your entire hybrid data estate is required.
Modernizing the roles of your data stakeholders: Key stakeholders have expanded beyond the traditional experts employed by IT. Data experts live in the business. Data scientists in the business team are embraced, but data governance stakeholders have yet to receive the formal recognition they deserve. The data owners are business people. Formalize security and data governance objectives early. Empower your business data stakeholders to perform those objectives in a scalable and automated manner.
Modernizing your data governance processes: Gartner speaks extensively of the evolution of data governance from dictated (IT command and control) to distributed (everything left to be performed at the edges of the process). Implement a blended model where the system is based on federated responsibilities with centralized control and auditability.
Unified data security governance
AWS, Snowflake, Databricks, Azure and Google continue to deliver more choices on their ecosystems, which offer more opportunities for your business. But more choices inherently increase the difficulty of enforcing security across this increasingly diverse landscape. The only way to future-proof your analytics along with your security and privacy posture is through a unified data security governance approach. Privacera was co-founded by the innovators who led the charge in creating Apache Ranger™, one of the most widely used open source data security and access control frameworks. As the only scalable data policy management solution based on open standards, Privacera offers a proven way to future-proof, while preventing vendor lock-in. Read more about the immense benefits of a data security platform based on open standards.