Leveraging Cloud for Modernizing Big Data Infrastructure

Leveraging Cloud for Modernizing Big Data Infrastructure

Modernizing big data infrastructure is a crucial step for organizations on the road to digital transformation.

Since transformation requires enterprises to seamlessly integrate the digital aspects of their business to enhance customer experiences, operational efficiencies, and organizational performance, such modernization will allow them to become agile and respond to disruptions in the industry. One of the easiest (and most successful) ways of doing this is by leveraging the cloud. When fueled by cloud technology, organizations can propel innovation and drive growth through digitally enhanced offerings, operations, and relationships.

The need for modernization

As organizations struggle to cope with exploding volumes of data generated by systems, customers, and processes, harnessing the power of big data is critical to business competitiveness. Big data can not only enable insights but also strengthen enterprise-wide decision-making.

However, for big data to really work, organizations need a combination of a cohesive strategy and powerful technical capabilities, so they can gather, store, and analyze structured and unstructured data sets. They need to approach big data in a way that helps them reduce infrastructure costs while improving capabilities, flexibility, and collaboration.

Given the cost (and effort) of maintaining legacy databases and the inability of such systems to handle the requirements of digital enterprises, big data modernization has become essential for organizations. It can help them better position themselves to curate and analyze disparate data streams and deliver real-time insights.

Modernization of the underlying infrastructure and strategies can enable organizations to:

  • Re-architect, revamp, or retire systems and processes that come in the way of business decision-making.
  • Deploy scalable, cost-efficient infrastructure to improve big data capabilities
  • Improve productivity and efficiency of the millennial workforce while empowering them to drive change through data
  • Seamlessly manage growing volumes (and velocity) of data and improve time-to-value
  • Keep pace with the ever-changing regulatory landscape and adhere to compliance requirements
  • Reduce latency of analytics engines and enable faster insights

Leveraging cloud

With the myriad possibilities that big data introduces, coping up with the sheer volume of data requires organizations to embrace modern technologies to crunch the ever-expanding analytics workloads.

Cloud enables organizations to scale data storage and analytics capabilities to the degree demanded by the digital era – what traditional, on-premise infrastructure just cannot. It helps them extract strategic business value from disjointed data sets, drive operational efficiency and agility, optimize customer engagement, and create sustainable competitive advantage in the digital era.

Big data modernization can improve flexibility and collaboration, providing quick wins for organizations. For companies burdened with technical debt from platforms that no longer add value, modernization paves the way for enhanced performance and scale. By providing anytime, anywhere access to analytics capabilities, it helps them meet the scaling demands of businesses – without having to manage or maintain the complex underlying infrastructure.

Here’s how you can leverage the cloud to modernize your big data infrastructure and increase the returns of your big data investment:

  • Identify areas of business where modern analytics capabilities can help innovate key services
  • Align customers (and employees) with the vision of an insights-driven enterprise, and define benefits they can achieve by leveraging cloud-enabled analytics strengths and capabilities
  • Evaluate every application’s underlying infrastructure and determine if they are better off on-premises, in the cloud or as a combination of both
  • Develop a strategy roadmap and determine how next-generation operating models will evolve as big data capabilities are delivered at enterprise scale
  • Outline the infrastructure requirements, define how you will go about the migration, and have processes in place to mitigate roadblocks
  • Understand the application development environment and accordingly scale-up or scale-out the infrastructure strategy
  • Have a robust governance strategy in place for managing and curating the ever-increasing volume of data, safeguarding data against growing threats, and continually maintaining data quality
  • Based on the requirements, develop a robust IaaS or PaaS strategy to re-imagine current systems, enable faster insights, and drive innovation

Become data-driven

Whether you are a CFO of a large bank or the CMO of a retail giant, harnessing the power of ever-mounting data sets is a challenge many are struggling to maneuver.

The road to a modern analytics strategy is often paved with the obstacle of rigid legacy infrastructure that restricts value while making critical business data inaccessible and unactionable. If organizations fail to quickly access, manage, distribute, and analyze available data while it is still valuable, they will be in no position to harness new potential data sources. Big data modernization using cloud can provide organizations with insights that help unlock new business opportunities. It can help build effective analytics ecosystems, instill a ‘data-driven’ culture to serve their customers better, outdo competitors, and increase their operational efficiency.

 


Radhika Achwal

Talent Acquisition Leader - Strategic Markets, ANZ & Global Cloud at Kyndryl

5 年

Great Article Anand!

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