Moving the data lake of an enterprise is not an easy process which you can automatically move your current data lake to the cloud. It requires relatively long procedures that need good leadership and a prudent approach, but it is still worthwhile to move into cloud infrastructures as it offers more advantages.  

Hadoop is an open-source software framework that redefines standards for processing and analyzing massive amounts of data, but with the emerging cloud computing technologies that provide more availability, minimum price, and simplified development, Hadoop storage is dead due to its complexity and cost. 

Cloud service providers like Microsoft, Amazon, Google have powerful features to fetch, store, manage and interpret digital data quickly and more efficiently at a minimum price. The businesses that are already using Hadoop by investing significant amounts of money tend to move data lakes to the cloud platform to collect different forms of data and to transfer data stored in Hadoop to cloud platforms over time. The start-up companies are directly moving into the cloud by collaborating with data service providers and opt-out of Hadoop entirely. 

From this article, we consider giving six reasons why you should switch your enterprise data lakes to the cloud network.

Related post – Why is Data Lake a Viable Solution in Big data Space?

1.Cloud computing security and governance

Within the on-prem data lake storage like Hadoop, data protection and confidentiality can be problematic with too many resources and individual data access, authentication, and encryption. Hence, the Hadoop structure necessarily involves the appropriate level of experience while cloud providers offering authentication and compliance standards as a part of their infrastructure as a service (IaaS). But the security of your data lake should not be left solely to cloud vendors. Every employee in the organization must accept responsibility for data protection and privacy. 

However, security requirements vary depending on which cloud provider we use, so it is necessary to consider how we will maintain consistent data governance policies in a hybrid or multi-cloud environment – something a data management framework will help us with.

Fortunately, most of the major cloud vendors have answered security and regulatory requirements, but it is a good idea to learn more about what they have to give and how we’ll interact with them for seamless security. One feature to look for in our cloud provider is that data is encrypted both in transit and at rest.

2.The efficiency of cost

In cloud storage services, businesses simply outsource their data storage to mitigate the need for hardware and internal storage and the maintenance cost. The cloud platform enables them to pay for just what they use. According to some reviewers, the pre-paid concept has the potential to drive the business out of control. It is true to some certain extent as the cost must be carefully tracked. But when considering the reduction of hardware and most importantly, the cost for maintaining hardware and other components, the cloud platforms overcome those minor disadvantages. 

Infrastructures that are available on-demand based in the cloud remove the necessity of companies to invest in hardware components to stock and manage data and allows them to just pay for functionalities and storage they have actually used. They do not pay for maintaining hardware anymore, as well as the payments normally dependent on real storage and technical costs, with per-query billing, per-month billing, etc.

Many of the applications that power data lakes of cloud infrastructure are cloud-based and serverless, allowing businesses to get up and running quickly and for less money by only paying for whatever they require. 

Although prices must be carefully tracked, the reductions of costs in engineering, skilled talent, patented hardware, as well as many expenditures greatly overcome this possible disadvantage.

3.Less complexity when compared to an on-prem data lake.

The on-prem data lake storage like Hadoop are extremely dynamic and costly to maintain. Because of its complexity, it requires comprehensive Java skills and experience. This situation can easily overwhelm the organizations by its steep learning curve and the time and money it requires. The data lakes based on cloud platforms are very convenient, accessible and user friendly. Cloud platforms demand less technical expertise when comparing to the Hadoop platform. As a result, it provides high qualified resources for a lesser cost. 

4.Scalable

In an on-prem data lake, to accommodate increasing data sets or new users, expertise must put a considerable amount of adding and setting up servers on a manual basis. Cloud storage has more flexibility and scalability. If the existing storage is not sufficient, the enterprise can upgrade the service plan and additional functionalities without transferring data from one location to another. Cloud providers allow enterprises to extend data lakes elastically despite increasing maintenance and operational costs. 

In reality, public cloud providers’ IaaS solutions are now providing auto-scaling capabilities, allowing organizations to maximize resource usage automatically on the basis of rules and conditions they define. They establish the lowest and the highest instances to guarantee that applications continue to run without going over budget. 

Most of the systems that are used today enable data lakes in the cloud, as well as cloud networks, are more scalable. On-demand and ‘pay as you go’ solutions are also available through software-as-a-service solutions, which can quickly extend top to bottom to accommodate increased data rates and users who do not require additional execution or hardware/software frameworks.

5.The advancement of technology 

Moving large data sets from data sources to on-prem data lakes is extremely difficult with their traditional data integration tools and load architectures. The enterprise users are dissatisfied with the long response times it takes when analyzing a large amount of data. The cloud environment supports advanced technology infrastructure covering almost all the aspects of data integration, transformation, aggregation, data visualization and business intelligence (BI). Also, cloud data lakes are preferable for deep learning methodologies which are needed for AI and machine learning algorithms. 

Today’s cloud data lakes are backed by a more advanced technology environment that covers the entire data journey from source to destination, including data integration, transformation, aggregation, and business intelligence and visualization. These cloud-native tools are designed to handle the variety, volume, and speed of today’s data. 

Cloud data lakes are also better suited for the complex deep learning needed for artificial intelligence and machine learning applications.

6.Opportunity to focus more on generating revenue.

The businesses’ ultimate objective is to generate more revenue. With the use of a cloud environment, enterprises can entirely focus on their business relationships. The growth of revenue as the cloud platform is taking care of the technological aspect. As a company, you must decide which systems could use to communicate with the cloud and which databases must be transferred from the cloud platform to on-prem data lakes like Hadoop. The transferring mechanisms of data lakes can be more expensive, while the cloud storage facilities are less costly. 

Most people were forced to reconsider the standards data as a result of the Hadoop revolution, but cloud computing continued to make substantial progress, and the model ofIaaS is only growing in popularity, increasing the efficiency of individuals as well as budgets of most of the companies.

The old paradigm of advance on-prem data storage and sorting are becoming apparent to be an expensive and time-consuming mechanism for which finding qualified personnel is becoming increasingly difficult. Organizations will soon realize a substantial saving of money and time by transferring those procedures to cloud platforms and creating a more effective and trustworthy data management application.

Conclusion 

Cloud services received significant attention over the past decade due to their up-to-date modern functionalities and ease of use. Now, most of the giant tech companies have their cloud services. Data is the fundamental and most powerful weapon in every organization. The inability to manage the data appropriately can cause organizations to fail. For those who are frustrated with the existing data lake ecosystem or that are considering moving to the cloud, this is the time to step forward. Investing significant time and cost in the cloud sector will not fail your organization but gives you the potential to manage your data efficiently and more reliably.