As more organizations across all sectors increasingly use data and technologies like artificial intelligence (AI) to further their business goals, many are discovering their legacy infrastructure is not up to the task. Isolated data silos and complicated workarounds can result in delays, increased operational costs, and risks to functionality, compliance, and security.
In the face of such challenges, some organizations shift to hybrid solutions that combine cloud and on-premises environments. But these platforms may not solve the problem if data cannot move seamlessly and quickly among environments, or if data workloads must remain on its existing infrastructure due to compliance or governance requirements.
In addition, settings and regulations for security, compliance, and governance may vary, requiring additional steps to ensure data is clean, complete, and safe. That can tie up limited IT resources and cause delays. These solutions also might not be built to handle the volume and complexity of data required for accurate analytics and AI model development.
A more effective approach is a “true hybrid” platform: one that connects data workloads across environments so the organization’s data—and the AI and analytics that data feeds—can move easily and operate securely. The results include increased operational efficiency, expanded computing power, and enhanced performance, unlocking opportunities for scalability and growth.
The Data-Powered Business Environment
Data availability and quality are the biggest challenges to achieving AI at scale, according to more than a third of IT leaders responding to one recent survey. More than half of these respondents said governance and compliance are also barriers to achieving end-to-end data management.
True hybrid supports consistent functionality and security across all environments without manual intervention. Anchored by a single platform, true hybrid capabilities can manage the data load, data management, and computing demands of analytics and AI quickly, securely, and reliably across cloud and on-prem environments.
“True hybrid delivers more than simply deploying to many infrastructures in isolation—it lets data, analytics, and AI move seamlessly between all, to handle change and always be able to deliver insight and value in the most optimum manner,” says Andrew Brust, Industry Analyst, Blue Badge Insights. “To achieve this, enterprises need a scalable, flexible data architecture that can grow with them.”
True hybrid comprises several key elements:
• A distributed cloud model. In this architecture, cloud services that are spread across various data centers, clouds, or edge computing sites operate as a single platform. This allows centralized control over operations and updates even when cloud services are in different locations.
• Portable and interoperable data services. The platform should let users easily move data and workloads among various systems. Those systems should be capable of seamlessly and automatically communicating and exchanging at each stage of the data life cycle, including ingestion, transformation, warehousing, and machine learning.
• Consistent data security, compliance, and governance. A unified and centralized platform lets organizations apply and enforce one set of policies and access controls across all environments.
These elements bring a host of advantages. Eliminating the need to manage multiple configurations and systems for security, compliance, and governance streamlines processes, easing the strain on internal resources, lowering IT costs, and reducing the risk of manual errors.
This is especially critical as businesses grow. One global consumer credit company found itself trying to manage more than 200 data warehouses for tens of billions of transactions every month, resulting in technical hurdles, increased expenses, and varying data restrictions from local governments. These obstacles prevented its growth and expansion into new markets.
After shifting its approach to a true hybrid model, the company reduced operational challenges and personnel training, lowering operating expenses by almost $200,000 per month. And with fewer barriers to expansion into new international markets, the business is experiencing revenue growth of nearly 30%.
While true hybrid platforms optimize existing operations, they are also essential to powering the vital data-driven decision-making and innovation to function in an increasingly fast-paced global market.
IQVIA, a provider of advanced analytics, technology, and research services for the life sciences industry, needs to quickly analyze data for insights: a serious challenge for its previous platform, with data spread across 250 warehouses.
Adopting a true hybrid strategy helped the company eliminate long waits to copy and move its data from one siloed location to another. Improved performance enabled faster analysis of larger datasets, helping IQVIA speed up clinical drug trials and development so it could more quickly and efficiently bring potentially life-changing medications to market.
True Hybrid: The Path Forward
A true hybrid platform brings advantages beyond making business operations more efficient and cost-effective. By removing siloed data challenges, enhancing performance, and supporting scalability, the true hybrid approach is an essential platform approach for organizations that seek to optimize their data for more accurate planning and robust data-driven insights that drive business innovation and growth.
Discover how close your enterprise is to attaining true hybrid with your existing data and analytics approach.
