Unlocking the Full Hybrid Cloud Potential With Modern Data Management

The pressure is on for businesses today. Staying ahead of the pack in terms of innovation is critical, and the best way to do this is by leveraging the preexisting data they possess. While often repeated, it is no less true that data is every business’ most valuable asset. Even when it comes to harnessing the full power of emergent technologies such as artificial intelligence (AI) and machine learning (ML), those algorithms and training engines are only as effective as the data they are fed.

For many businesses, however, the main sticking point is in how they manage data flows. It used to be that businesses stored data primarily on highly secure, on-premises systems. But this is changing as the growth of the cloud has pushed many to explore a hybrid approach. According to research by Alibaba, this hybrid cloud approach is on the rise in Asia. The e-commerce company found that 39% of cloud strategy switchers have pivoted to a hybrid cloud approach. Decisive factors in this trend were security and added flexibility for organizations to customize their cloud deployments. Crucially, though, the key to driving business outcomes and leveraging the benefits of a hybrid cloud approach rests on modernizing mainframe systems and implementing the right data intelligence tools.

Unlocking data risk-free

New challenges arise as businesses look to harness data in the varying environments that characterize the hybrid cloud. Taking business data and migrating it to new, cloud-based environments poses an essential question: how can the organization manage it holistically? While by no means straightforward, the first port of call for businesses should be modernizing data infrastructure.

Protecting data along its journey to the cloud requires complete visibility. Legacy systems often create data siloes, making it difficult to see what’s happening in a given corner of the business. When modernizing, companies should prioritize solutions that allow for siloes to be eliminated. This ultimately offers decision-makers a picture of their data across the entirety of the enterprise. Furthermore, due to the sheer volume of data in the hands of today's typical business, software solutions that bring agility and flexibility to data management are also a must. Hybrid migrations can facilitate frictionless modernization. However, continuous, successful transformation hinges on ensuring the business is equipped with the right tools in its technology stack to drive this objective.

This emphasizes the point that for hybrid cloud strategies to result in successful modernization, deep visibility and strong controls on data in transit is crucial. Understanding its provenance, guaranteeing its redaction, and reporting consistently on the success of compliance and governance efforts are core functions that now must extend to the cloud. With established, effective data practices, organizations can more freely interact with their valuable and critical data without incurring risk.

Future-forward data management

Modernizing data management processes is crucial for businesses to become data-driven, future-forward organizations. Not having the tools to automate data management will result in a failure to capitalize on the data businesses have in their hands. By removing the human element from some aspects of data management, errors arising from high volumes of information can be minimized.

Cutting down on waste is also critical for content management. Rocket Software’s Movement to Modernization report revealed that 34% of business leaders felt redundant and unnecessary data was their biggest content management challenge. This obstacle can be overcome via a centralized approach that gives data professionals the tools to sort and classify data. As a result, it becomes easier for IT teams to spot and eliminate redundant, obsolete or unused data, cutting costs and making higher-quality data more discoverable and, thus, more actionable. Teams can leverage data intelligence tools to centralize their data management to improve workflows and overall decision-making. 

A data-first approach to business

Innovation is critical to thriving in today’s business landscape. However, being able to innovate in a meaningful and impactful way rests on the quality of the data behind it. For any business to stay ahead of the market, success hinges on its data. Getting that data into cloud AI and ML engines has the potential to generate groundbreaking insights. But that task is more complex than it may seem at first. On-premises systems keep data tightly secured, and opening new doors can introduce risks.

The dichotomy of trying to innovate while protecting enterprise assets puts the onus on businesses to closely examine the state of their data management infrastructure and processes. Modernized data management offers a resolution to this tension. Through data intelligence technology and content automation capabilities, organizations can harness the full potential of their data while mitigating the security and integrity risks of a hybrid cloud system.

Praveen Kumar, vice president for Asia Pacific at Rocket Software, wrote this article.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/Trifonov_Evgeniy