Introduction to Cloudera And Amazon Web Services
There are many types of big data applications, and the number continues to grow as it will promise the growth in COVID time remains a strong trend for organizations around the world.
Finding the right kind of application for your specific needs can feel overwhelming, especially if you aren’t completely certain about what you want the application to do for your business.
“Your best approach is to characterize your objectives clearly at the start and then go searching for items that will assist you to reach those objectives,” says Cynthia Harvey from Datamation.
After doing this, it’s easier to match application features to what you want to accomplish with your big data.
Make Key Choices First
Before shopping around, it’s best to get a few things straightened out in regards to your big data needs. This includes deciding on:
Where will the Data go?
Do you want to store your data on-site or in the cloud? Working from either has both positives and negatives. On-site gives you more control over compliance regulations and security, but the cloud systems provide easy scalability and management.
Cloud-based storage also doesn’t often require an on-site technician which can make them more cost-effective.
Will you opt for Open Source?
Open-source software is usually much less expensive to own. Proprietary options can come with large license fees in addition to you needing to purchase special hardware.
That being said, open source can be harder to work with. Issues with configuration can lead to the need to hire a consultant which then increases the cost.
How important is Streaming?
Traditionally, big data was analyzed in batches, collected before the application could review it. Today, real-time analysis is becoming a more constant feature of big data applications through streaming.
While it’s not yet for everyone, having the ability to stream data is increasing in popularity because it can give an organization a competitive edge when looking at their data.
Meet two major players in big data
Two key players in big data applications are Amazon Web Services (AWS) and Cloudera. Both of these options provide users with access to tools and resources that make it quick and safe to process large quantities of data, but how do you differentiate? you can also check out aws big data course.
Amazon Web Services
AWS is a compilation of processing services that help to build, verify, and deploy big data. Operating solely in the cloud, this is an attractive platform for businesses because there’s no infrastructure cost.
You don’t have to have on-site hardware, a technician to manage it, or set aside a budget for repairs or upgrades. New items are added regularly to help leverage the latest technology for working with big data.
Where AWS is a broad collection of services that collect, store, process, analyze, and visualize big data on the cloud, Cloudera is a much more specific platform.
Scalable and flexible, it allows you to easily manage large volumes and varieties of data. Containing the necessary components to process big data, Cloudera helps organizations focus on utilizing the results of data analysis.
What you can do with data using Cloudera goes deeper. You can easily analyze it while tracking and securing information across any environment, but you also can conduct comprehensive audits and lineage tracing.
You not only see the data but can understand where it came from and get a better understanding of why it matters. This stronger connection to the data then makes it more useful for your organization.
Pick more than One
Many organizations are shifting to a hybrid cloud approach when it comes to storing and managing large quantities of data.
This enables them to have both an on-premise environment and one in the cloud, increasing agility. “In a recent study, 451 Research found that over 60 percent of companies either have a hybrid cloud strategy in place or are actively deploying pilots,” says Cloudera.
This means you don’t necessarily have to pick between using applications like AWS or Cloudera. You may have the ability to use both.
Using Cloudera on AWS can help add value to the data living in the cloud. Whether working with data in an on-site repository or the cloud, Cloudera can help rapidly process and explore data to transform it into analytics to drive customer insight while reducing business risk.
The data can inform on product development to help create better products and services as well. Combining the two platforms enables organizations to benefit from both: greater flexibility and cost-efficiency.
The two specific Cloudera products most helpful within the hybrid cloud environment are:
- Cloudera Altus which functions as a platform-as-a-service, making it easy and cost-effective to process large-scale data within a cloud environment.
- Cloudera Altus Director improves deployment and management for the lifecycle of Cloudera Enterprise clusters functioning on AWS. It is available through the AWS Marketplace as well for even easier integration.
Find the Right Big Data Application
Regardless of whether you use big data services or rely on a mixed approach, the key is to align what you use with the goals of your organization.
The best way to do this is to know what you want to accomplish. Establish the features you need in your software and fully research what’s available and most cost-effective before settling on anything specific.
