Big Data analysis systems have reached their edges with the growing sizes of data they should process and analyze. Every day, the systems should deal with data processing and analyzing up to the size of Exabyte. The “offline” infrastructure or on-premise data processing of Big Data that host the operation and workloads seems to have reached the limits for covering huge data size and consequently required switches to the alternatives.
Today, migrating Big Data processing to cloud is seen as the main solution to optimize the processing. The Cloud infrastructure allows a flexible yet scalable Big Data processing with high speed. While more companies have been migrating Big Data to cloud, the practice of big data cloud migration still faces some challenges. However, at this very point, there are best migration practices you can take advantage of. Keep reading.
Fundamental Reasons for Migrating Big Data to The Cloud
Not only the size or volume but the variety and velocity also define data as Big Data. The processing of such big data demands continuous development to accommodate the massive volume. The innovation in databases is fundamentally required to cover dynamic changes. In general, a big data cloud migration enhances the performance, velocity or speed, and makes the Big Data processing scalable.
Cloud services come with updated infrastructures powered by latest memory, processors, and other hardware. On the other hands, cloud services are compatible and work friendly with both Linux and Windows, two top Big Data environments. Data processing would run smoothly with no obstacles when using cloud services.
When you migrate Big Data to cloud, one obvious advantage is that you’d make the processing scalable. Whenever the traffic reaches the highest point, the data processing would scale up and accommodate massive amounts of data with no problems. Depending on the cloud services, they can scale up to Petabyte-size processing or add new nodes.
Overall, cloud services offer a more cost-effective yet manageable and accessible Big Data operation. Their updated hardware and software offers a more efficient infrastructure. You can save a lot of money that you’d have to spend for on-premise Big data processing.
Factors to Consider on Big Data Cloud Migration
While it’s highly advantageous and beneficial, Big Data Cloud Migration has some challenging factors you should consider.
The big data cloud migration comes with a data security challenge during the process. The current preliminary precaution or the solution is to separate the computing and the storage to protect sensitive data, it’s called the hybrid solution. Another solution is to implement authoritative access control to manage cloud data accessibility while keeping them protected.
Skills of Data Practices
It’s not a secret that big data cloud migration isn’t a plug and play solution. The migration process itself requires comprehensive knowledge, sets of technical skills, and proper tools on data practices. It’s because the developers not only migrate the data from on-premise infrastructure to the cloud service but should also connect the data sources with cloud environments for Big Data.
While the migration results in cost-effective operation, the migrating process itself could be costly. The code-writing process to accommodate the movement of data traffic could be a tedious task that requires continuous,regular monitoring and adjustments to any error. We’re at the stage where the migration can’t be done with automation, code writing environment. Overall, the Big data cloud migration process is resource-consuming.
Migrating Big Data: Where Are We Knowing?
The migration of Big Data to the cloud services have been continuously developing. Developers are working on the best, most efficient Big Data cloud migration practices. By far, these are some best migration practices you can do.
1. Involve Heads of Organization
When it comes to a company’s Big Data cloud migration, all heads of the organizations should be involved. This includes CEO, managers, IT departments, heads of divisions, and relevant staff. Their involvement would inform which data can be migrated to the cloud and the ones shouldn’t be so that they become important inputs for your migration strategy.
2. Recognize and Manage The Loads
Companies should recognize their capacity in accommodating Big Data cloud migration. The major solutions include storage, development and processing but doing all threes are not all companies can accommodate. By recognizing your loads and capacity, your developer can design the most suitable migration strategy.
3. Manage a Cloud Migration Design
There are currently three major Big Data cloud migration strategies including Lift and Shift, Refactoring, and Re Architect. If you want to move data and apps into the cloud without any changes, Lift and Shift is your strategy option. A refactoring strategy should be applied if you want to make changes on data processing or repurpose software. If you want to make Big Data fully compatible with the cloud environment and as data modification is inevitable, you’d use the Reachitect strategy.
4. Determine Security Measures
Migrating Big Data requires you to monitor and secure data during the process and the implementation. The existing security measures should adapt the cloud service where Big Data migrates into. Some cloud platforms have specific requirements you should comply with your security policies. The should determine the security measures and controls at the very beginning of the migration process.
5. Select The Most Suitable Cloud Service
As you might have known that cloud service or platform may have a spectrum of requirements. These include performance, development, data warehousing, testing, analytics, and so forth. Complying these requirements would affect your migration strategy. Assess the services provided by the platform and choose the most suitable ones.
Migrating data to the cloud environments could be inevitable in the future especially for those companies or businesses that rely on Big Data operation. Cloud-based Big Data operation would improve their marketing and data-driven business decisions. It’s beneficial for small, medium, and big companies. A Big Data cloud migration could be challenging and resource-consuming in the process but it would drive major benefits for business in the long run.