The Necessary Steps to Improve Data Management in the Cloud
As business technology modernizes, data’s role in monetization has dramatically increased. It’s no surprise organizations have connected their overall success to the effective collection and use of data. However, it can be a challenge to maintain proper data posture in the cloud as data sprawl or siloes are common pitfalls. Additionally, there is now increased scrutiny of data never experienced before. The essence of data is constantly expanding, which has constructed a significant problem for many businesses in collecting, storing and leveraging information.
Here are three tips to help improve your organization’s data management in the cloud:
Always look ahead
Once you migrate to the cloud, your job is nowhere close to being done. The moment a migration is complete is when the real work starts. Tracking and controlling costs, keeping up with the evolving security landscape and optimizing overall performance become critical parts of the process. Below are some questions that must be answered ongoing:
Where will data live and why?
How will data be collected, cataloged, and leveraged?
What is the established process?
Do you have a master data management strategy with supporting security structures in place?
Businesses should have a clear strategy and delegation of tasks in place to answer each question. The major cloud players like AWS and Microsoft Azure, provide native tools in their environments that can help accomplish these goals. If your company doesn’t use either of those platforms, there are also many non-native solutions that can be used in any public cloud. No matter the solution it’s always smart to seek counsel from a cloud managed services provider who will identify possible improvements, underused resources, and solutions that align with organizations’ goals.
AI/ML accelerating a business’s time-to-value
When collecting, storing and analyzing data, artificial intelligence (AI) and machine learning (ML) can play a huge role. By using AI and ML, businesses are able to monetize information at a faster, more effective rate. In order to get the most out of AI/ML, data must continue to be easily accessible without sacrificing security, making the cloud a perfect option.
An increase in flexibility, scalability and speed are just a few of the advantages displayed by the public cloud compared to a pure infrastructure system, which cannot operate at the same level. The cloud combined with a successful AI/ML strategy allows companies to accelerate their value to levels never seen before.
Add a solution provider to your team
When operating in the cloud, one common challenge that often boils to the surface is finding the right personnel while ensuring business-critical objectives are still top of mind. Many organizations are used to maintaining on-premise data centers, creating a skills gap when moving to a cloud infrastructure.
Candidates with cloud-focused experience are hard to come by, so many organizations look for external help from solution providers. Cloud managed service providers are experts on completing seamless, secure cloud migrations, and can help develop strategic plans to migrate only the necessary data based on your business’s needs. According to Emergent Research and Intuit, 80 percent of U.S. small businesses will deploy cloud computing in 2020.
Preparing for the future
If the past year has taught us anything it’s that businesses can never be too prepared for the future. When looking ahead, it’s critical to keep in mind the continued role the cloud will play for competitiveness. As part of this planning, identify the best strategy to leverage the cloud’s benefits — flexibility, scalability, security, and accessibility. COVID-19 has increased the rate of change in the modern business landscape, meaning cloud consumption is no longer a run-of-the-mill tool: it’s essential.