With data, an organization can do super powerful things with AI and machine learning, like building models that do everything from enhancing fraud detection capabilities to identifying gaps in the market for the organization to separate from the pack.
But getting to that data, and using it effectively and securely, is often easier said than done. Real challenges and complications can arise with respect to managing data flows across the enterprise. The potential risks that come with moving data into the cloud when it had spent its entire life on highly secure, on-premise systems can open an organization up to new, previously unknown vulnerabilities.
According to research firm Forrester, 94% of U.S. enterprise decision-makers are actively using at least one form of cloud deployment in their own organizations. And a survey conducted by Rocket Software found that 93% of IT leaders view hybrid cloud as the future of IT. As cloud, and hybrid cloud, continues to gain favor in businesses for its agility and resiliency, managing data flows is a process that cannot be ignored.
With the right solutions, practices, and processes, businesses can feel confident that existing data is housed in the right environment and has the biggest impact. Here are three ways organizations can gain a competitive edge and harness the full potential of their data.
Bring modernization to data management processes
Before a business can fully tap into its data, IT leaders need to get a handle on the processes within the organization, and that should start with a full modernization effort. Particularly, businesses should be incorporating contentworkflows, redaction, governance, and metadata management into the core processes that are controlling data management. Modernizing these areas and streamlining processes invites more opportunities for automation, reducing the need for human involvement in certain aspects of data management. With human involvement reduced, IT teams can reduce strain and eliminate or mitigate the risk of human error within data flow.
Streamlining processes and eliminating waste is critical, especially when it comes to content management. The sheer volume of content and data that exists within organizations is already a massive undertaking to manage. Any IT team should prioritize finding opportunities to identify, and eliminate, redundant or unnecessary data and content whenever possible. The best way to tackle this problem is by taking a centralized approach to content management. Incorporating data intelligence solutions improve workflows and decision-making. But more importantly, it gives data professionals a better understanding of the current state of their organization’s content and gives them the right tools to accurately sort and classify data.
2. Do away with silos once and for all
Data siloes have long plagued enterprises large and small. When visibility is limited, modernization efforts can end up taking the hit, moving slowly and in some cases, happening in pockets totally unknown to the rest of the organization. For a business looking to tap into its internal data, once data starts to move between environments, it’s critical to know exactly where everything is going.
Solving this challenge requires an organization to rethink and modernize its data infrastructure. Hybrid cloud migrations present an effective path forward, but doing so requires the right technologies in place to make it happen. Leveraging software solutions that offer agility, flexibility, and visibility to data teams has become non-negotiable. Beyond the solutions that are folded into operations like AI and ML models, businesses also need to overhaul data practices as well. Compliance and governance are core to the success of data and content management processes. Modernized data practices allow IT teams to interact with critical data more freely while remaining secure from undue risk.
When it comes to breaking down siloes, it’s also important that the data within an organization is accessible. It’s one thing to know where everything lives but if the employees that need that data don’t have the tools to access it, there’s little value being generated. With a tool like Rocket Data Intelligence, users throughout the enterprise are empowered to do otherwise complex data analysis and gain insights that can transform not just their departments, but the entire business as well.
3. Delivering better outcomes through data
No matter the industry a business finds itself in, the broader market is only getting more competitive. Survival has become dependent on how well an organization is able to adapt and innovate. That innovation is directly tied to data, and a business’s ability to access and harness it. By modernizing every element of existing data flows, processes, and practices, businesses can more effectively feed internal data into powerful AI and ML engines to generate crucial insights that keep them one step ahead of the competition.