Moving an existing data lake to a cloud environment or building a brand-new data lake on the cloud, requires a great deal of work. Understanding what potential obstacles can present themselves and how to overcome them will help ensure a smooth transition. The aim of this article is to shed some light on how to achieve this.
Common internal challenges to cloud data lakes
For many businesses, the biggest obstacle is not technical, but rather working through business-specific issues. Here are a few challenges that many CIOs or storage managers need to address to make this move:
Budget predictability – In almost all cases, the total costs of a cloud data lake will be lower than an in-house solution. The costs of a cloud solution, however, fluctuate based on per-hour billing, which can make it a difficult sell to the ultimate decision-makers. Our dedicated consultants can help simplify the complex costs for people at all levels.
Reorganizing talent – While executive level management often sees the value in reducing IT engineering costs, the idea of moving the management and support of a data lake to a third party can be difficult. This is especially true when seeking buy-in from team members across all levels. Based on our experience, most businesses do not have to lay off people after this type of transition. Instead, they are free to focus their talents on initiatives that directly support business objectives rather than just keeping the data lake operational.
Security – There is no doubt that a cloud data lake is more secure than virtually any in-house solution could possibly be. Due to high-profile data breaches, however, this can be a hard sell to some members of management. Our consultant can outline the modern security features that cloud data lakes provide in a way that both technical and non-technical resources will appreciate.
Common technical challenges to cloud data lakes
Technical challenges can be significant whenever a new cloud system is set up or an existing cloud system is transitioned. While data lakes are still a relatively new option for many businesses, the technology behind them is well-established. Some technology-focused issues that often need to be addressed include:
Transitioning existing data – You may have years’ worth of data stored in-house, either on an internal data lake or separately across multiple systems. Planning the best way to efficiently upload historical data to a cloud data link is something that our consultants specialize in. This can be done while also sending newly generated data to the cloud for production use immediately.
Internal analytics – Internal analytics tools often will not naturally transition to a cloud data lake environment. This is because the tools are either customized for an in-house data lake or more likely, separated based on siloed data storage environments. Fortunately, there are cloud-focused analytics and artificial intelligence tools available to better interact with data. Our consultant can provide any required training to ensure your users are able to take advantage of these tools.
Choosing a cloud host – We recommend using either Amazon Web Services (AWS) or Microsoft Azure – the two largest cloud platforms in the world, and with good reason. We are an AWS Service Advanced Partner as well as a Gold-tier Azure Managed Service Partner, so we can help create and manage an effective data lake on either of these popular options.
Choosing Trianz
We have helped businesses around the world with cloud data lakes and have seen just about every challenge you can imagine. We have the experience and technical contacts with both AWS and Azure to successfully navigate any cloud transition.
