Why Companies Need a Flexible, Scalable Cloud System
With the prolific growth of data, companies are looking for retention solutions that better match their everyday needs. Today’s businesses feel a cloud solution is their golden ticket to more control over their data and that it involves less monetary investment than a data center, server-based solution. At the same time, companies are also finding that data storage is an increasing issue. In fact, 60 percent of companies are putting aside money earmarked for additional, secured storage space for their sensitive data.
While a cloud solution may provide additional security, scalability and flexibility, one issue remains and that is the ability of employees from the C-suite to the IT department to manage the cloud itself. Whether there’s a security breach or simply routine maintenance to be done, your team needs to respond to each issue with the right knowledge and company-wide-approved plans. Without knowing how to best use a cloud storage platform, IT may scramble to find another secure, usable file-sharing system, leading to potential data security issues.
Educating your IT department and overall company on a cloud solution can mean the difference between a business going forward and holding itself back. A new on-site data center can take a year to build and become outdated right when it opens, leaving your business behind when it comes to storing or scaling back on data as needed, locked into a hardware solution where you’re paying for 800 gigs of storage when you only need 550 one month or 975 the next.
In order for companies to make this happen, here are the five best practices for creating a flexible cloud system that your employees can build, maintain and scale over time.
1. Moving to a Cloud Solution Requires the Right Training
Data migration, or moving data to a new storage platform, can be a headache if employees haven’t been properly trained on how to do it. What’s more, it may be a necessity if your company’s physical server or data center’s hardware is beginning to age out. If something happens to the server, you can’t move your data from A to B all at once.
Moving from a server to a cloud needs to be done as part of a well-informed, step-by-step process while understanding time is of the essence so businesses can stay competitive. In fact, 56 percent of businesses surveyed in IDG Enterprise’s 2016 Cloud Computing Executive Summary said they were working to transfer more of their IT operations to the cloud. Per that same survey, 70 percent of U.S. organizations are using private, public, hybrid or a mix of these cloud solutions, a figure that’s expected to increase as more businesses use cloud solutions.
The solution is to find training for employees that helps them make a blueprint of the process in waves, mapping out certain dependencies in the data to ensure a complete, secure transfer. They’ll need to understand scalability, i.e. how to put in a small workload to start and then expand once the new cloud environment is functioning correctly.
2. Maintaining and Knowing Different Types of Cloud Solutions
All clouds aren’t created equal; many different cloud configurations exist, including multi-clouds, hybrid or hybrid IT solutions. Your company may have more control over a hybrid solution than a public cloud. Looking into a hybrid IT solution, defined by The National Institute of Standards and Technology as “a composition of two or more clouds (private, community or public),” there are many different deployment methods. Hybrid cloud solutions have been shown to provide the best of both worlds for companies, where they can use public cloud services while maintaining their own private cloud networks. In fact, hybrid cloud solutions will be part of the huge growth seen in the data analytics market, reaching $203 billion as soon as 2020.
But some companies want to only dive into public clouds instead of evaluating the value of a hybrid solution. Oftentimes, they’re eager to use the scalability and flexibility of public clouds right away. This is yet another reason why employees need to be trained on the different types of cloud solutions to find one that best matches their company’s need instead of the trends.
3. Combining Seamlessly with Other Data Elements
The interdependence between cloud computing and other emerging areas of tech will also become more important. The combination of big data analytics, cloud computing and machine learning is poised to create “a new class of infrastructure network analytics” that provides a more holistic view of the network and attached devices of the data running through it. This is especially true for businesses where ecommerce plays a large role.
With this in mind, employees must understand the interdependencies of these systems so their company clouds can run smoothly and securely. They must be aware of where the connections exist, and in the case of mapping out data transfers, understand where they go.
4. Considering the Needs of Different Industries
As the pace of cloud computing continues to increase, different industries will have more unique needs when it comes to storing, maintaining and using their cloud platforms. In the healthcare industry, for example, healthcare organizations need a cloud-based solution in favor of an on-premises one because of the sensitivity of the data they are holding. In addition to data sensitivity, datasets for certain research efforts can require huge storage needs; at the Icahn School of Medicine at Mount Sinai, physicians crunched up more than 2,000 DNA sequences during their research on breast and ovarian cancer, or more than 100 terabytes of data.
Employees must be comfortable working with such large and unique datasets and be prepared to go into planning mode, carefully curating the data so it can easily be stored and retrieved.
5. Learning and Retaining Cloud Data Expertise
Businesses can be one step ahead of the competition if their employees have full capabilities over their cloud platform. Not only will they have a leg up on other companies when it comes to storing sensitive data, money and time saved from a cloud solution allows them to make other necessary business decisions about additional add-ons, helping them grow even more.
To this end, quality training programs are available for employees to learn the fundamentals and get certified in managing cloud platforms. Some of these learning opportunities include the Google Cloud Platform Big Data & Machine Learning Fundamentals, high-quality training in big data and learning capabilities. The Simplilearn Google certified professional-data engineer certification training course is designed to teach employees how to use Cloud SQL and Cloud Dataproc for migration of workload, how to master interactive data analysis using BigQuery and Datalab, and how to train and use neural networks using TensorFlow. It will also help them understand data processing architectures, Task Queues and DataFlow. If employees need an introduction first, Google Cloud Platform Fundamentals Certification Training prepares them for incorporating cloud-based solutions into business strategies.
With these best practices in mind, your employees will be well-trained professionals on your cloud systems. From implementing to maintaining your cloud platform, employees will keep things running smoothly with an eye on security, scalability and flexibility.
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