As organizations increasingly leverage data and AI, legacy infrastructure struggles to keep up. Hybrid solutions may not fully address the challenge of seamless data flow and varied compliance requirements. A 'true hybrid' platform connects data workloads across environments for efficient operation and security, unlocking scalability and growth opportunities.
As more organizations across all sectors increasingly use data and technologies like artificial intelligence 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 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.
“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.
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.
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