That organizations who successfully generate business value from their data will outperform their peers is known to all. Yet, storing a massive pool of structured and unstructured data that is generated from internal transactions, customer interactions, social media as well as third party and publicly available sources has always been a mammoth task. Especially in an age where they have to run different types of analytics, visualization, processing, and machine learning algorithms to better guide business decisions.

Data lakes have long enabled organizations to efficiently store large pools of data and use it to make critical decisions.

According to an Aberdeen survey,organizations who implement data lakes are known to outperform others by 9% in organic revenue growth.

However, as data volumes grow, on-premises data lakes are losing their value; they are incapable of managing the unprecedented swell, often resulting in poor or lackluster business decisions.

Data Lake and the Cloud

Given the numerous benefits that data lakes offer, they are also the ideal workload to be deployed in the cloud. With cloud offering a diverse set of analytic engines, and massive economies of scale, moving your data lake to the cloud has a number of significant benefits including higher performance, scalability, and agility.

Here’s why moving your data lake to the cloud makes sense:

1. Access to the latest technologies:Having a data lake is one thing; using the right tools and technologies to analyze and process the data is another. Any upgrade requires you to spend a considerable amount of time since there are so many dependencies and aspects that have to be planned out. With the cloud, you no longer have to worry about what tools or technologies to use, to make the most out of data. You can get access to the latest tools and technologies and enable better and more timely decision-making.
2. Dynamic processing: The beauty of the cloud lies in the agility and flexibility it With the cloud, you can pay for just the resources and services you use and scale as you grow. This is what makes data lakes in the cloud a lucrative business proposition; you can not only enjoy access to the resources you need, when you need them but also pay as you go. What’s more, the cloud allows for dynamic processing of data – without you having to worry about storage methods or what tools to use to analyze critical business data.
3. Scalability: In addition to on-demand processing, the cloud also offers the much-needed on-demand infrastructure. With the ability to start small, and grow as needed, the cloud allows you to meet the spikes in demand, and cut back, whenever needed. Since you can access resources based on your business requirement, you can drive substantial agility and ensure you’re meeting business goals, out-doing competition, and keeping up with the times.
4. Compliance: As security and privacy become extremely critical for businesses looking to succeed, the cloud ensures your data lake is always compliant with the latest regulatory frameworks. With most modern compliance and regulatory requirements baked in, the cloud makes sure you never falter with respect to security, and seamlessly carry out business operations for improved customer service.
5. Business continuity: Disasters never come with a warning; they can happen anywhere, anytime. A big advantage of moving your data lake to the cloud is that most cloud vendors have exceptional data recovery strategies. So, whether your data lake resides in another region, country or continent, the cloud offers the much-needed resiliency to ensure business continuity – without a hiccup.
6. Cost benefits: When it comes to storage and compute, on-premises data lakes can be a costly affair. Not only do you have to make massive upfront investments, you also have to continuously purchase new tools, systems and analytics engines to process the data. However, that’s not the case with cloud. The cloud allows you to seamlessly operate your data lake – without worrying about infrastructure, storage or compute. With access to all the tools you need for analytics purposes, having the data lake in the cloud means you can get the most out of your data, and meet your business goals with ease.

Have a plan in place

Moving the data lake to the cloud is a massive undertaking and cannot be done in a day. And it shouldn’t be, since there are several aspects to be planned out, several challenges to be prepared for, and several remediation measures to be considered.

If you have made the decision to migrate your data lake to the cloud, here are some things to consider:

• Understand what the migration encompasses, and make sure to have a robust migration plan in place.
• Devise proper processes, and ensure the business understands the benefits you will achieve a successful migration.
• Screen a handful of cloud vendors, and choose one that best fits your needs – depending on the industry you belong to and the customers you serve.
• Understand how to structure your data lake architecture in the cloud, carefully strategize your migration, and choose a cloud environment that makes the most sense for your business.
• Select the right resources and people for the migration, and make sure everyone is aware of their roles and responsibilities.
• Always begin by moving a small workload first; only once you experience success with a handful of use cases should you move to the next phase.
• And lastly, constantly test the new environment so you know you’re not missing out on a critical aspect of the migration, or any vulnerability that can bring the entire migration down.

Better together

Data lakes have long aided organizations as a centralized repository to store all their data – without having to structure the data, and at any scale. But today, as data volumes sky-rocket, traditional, on-premises data lakes are no longer effective.

In a cloud-era, moving them to the cloud makes total sense. By providing a cost-effective, powerful, and agile environment for assembling, preparing, aligning, enriching, and analyzing diverse structured and unstructured data sources, data lakes in the cloud allow data to be interrogated by multiple people using multiple tools simultaneously. Data lakes on the cloud also free up data scientists and allow them to focus their efforts on more critical tasks.

Moving your data lake to the cloud allows you to identify, and act upon opportunities for business growth more effectively; you can get access to the latest technologies, enjoy dynamic processing of data, ensure scalability, compliance and business continuity – at reduced costs.