Cloud Computing is the way to store and access data over the internet. Using cloud computing, higher level services could be obtained with minimal effort. Extreme scalability is offered by cloud computing in comparison to the traditional hardware systems. Launched in the year 2006, Amazon Web Services or AWS uses Cloud Infrastructure-as-a-Service. Amazon Web Services provides computing power, data storage and other solutions to the organizations according to their needs.
It is not only difficult but time-consuming as well to build scalable infrastructure. In the modern generation, large applications deem robust infrastructure which is even more challenging. Cloud Computing resolves such scenarios by providing services over the internet. Amazon Web Services has eliminated the need to maintain on-premise private infrastructure. At AWS, you would only pay for what you use. Security is another area where AWS has made significant strides. There is no permanent data loss as Amazon Web Services has data centers all over the world.
What is Big Data?
Technology has advanced a lot in the past decade and so is the amount of data that it generates. The internet is the source of such volumes of data from a plethora of channels. Data got generated previously as well but it didn’t have the system to mine such voluminous data. However, the recent advancement in technology and the arrival of cloud computing such as Amazon Web Services has certainly changed the way we look at such huge volumes of data now.
Big Data stands for 4 V’s – Volume, Velocity, Variety, and Veracity. Volume refers to the large chunks of terabytes of data that’s getting generated while velocity measures how rapidly we are getting such data. Variety is the different channels which generate such data while veracity is the relevant meaning that it carries.
Now, to handle and analyze such data, it requires huge computational power or strong infrastructure to build applications which would cost a lot to set up such a system. Cloud Infrastructure such as AWS thus gives us a chance to utilize big data with the help of their services and work seamlessly without worrying about scalability or security.
Why AWS Big Data is the Best Career Move?
You learned about Big Data and saw how AWS provides a platform to utilize such data. Amazon Web Services is one of the go-to skills in the current market. Companies are gradually moving more traditional infrastructure set up to cloud to speed fast their process and increase the scalability.
Below are the ten reasons why AWS Big data is the best career move right now.
1. There is a saying that it is useless if you don’t have the skills to analyze it. Job opportunities in analytics and big data management have risen and so is the need to invest money and time to get trained in skills such as Amazon Web Services or AWS.
Moreover, with the analytics market set to conquer almost one-third of the current IT market, it is necessary that you train yourself with the relevant skills. The demand for professionals trained in AWS Big Data is high as organizations are looking out for various ways to exploit big data. Among US business, AWS big data is considered to be of utmost priority. As more companies are now moving towards cloud solutions such as AWS, Azure, it would enable them to get the best insights from such voluminous data.
2. To be a proven expert in AWS, you need to showcase your worth and get yourself certified. The AWS Certified solutions architect is one of the top level certifications’ at the associate level. On the Amazon Web Services platform, you would gain the experience of designing distributed applications and systems.
Additionally, it would teach you how to deploy big data applications and scale it up on the Amazon Web Services. Based on the customer requirements, what services you should use for your application. You would learn how to deploy a big data app in AWS. The other certification which you could acquire and would certainly help in taking your AWS Big Data career to the next level is the AWS Certified Solutions Architect-Professional course.
This certification proves your worth in AWS and could put you in a more advanced role in your organization. You would not only learn how dynamically scalable and reliable apps are designed or deployed.
3. The shortage of professionals who are expertized in working with Big Data in AWS is huge. On the supply side, there is a significant skill deficit. In terms of the global percentage, India has the number of analytics professionals. The talent demand in the field of Big Data Analytics and AWS is expected to grow in the future.
4. In addition, to maintain the infrastructure and build a seamless data pipelines, it is pertinent for Big Data developers to learn to code in order to build flexible systems. Thus to work with big data in AWS, it is necessary to get yourself certified with the AWS Certified Developer Associate certification.
It would provide you with the relevant knowledge to choose the Amazon Web Services package based on your application. From the application, the servers which interact with the software development kits could be made the most out of. You would also master the skills to optimize the big data system performances with the code. Moreover, security is one of the primary concerns when you are dealing with applications that are built on such volumes of data. Thus with AWS, you could add security to your big data application while still coding.
5. Amazon Web Services gives you full flexibility in controlling the flow of big data in and out of your AWS platform. In fact, on AWS, if you want to migrate on-premises big data application you could also do that. The operational cost control mechanism could be identified as well with the help of AWS.
Real-time feature is one of the primary needs while building a big data application. AWS provided the platform to do just that by managing and implementing continuous delivery systems and methods. The automation of the operational process of your application is another major advantage that Amazon Web Services provides. You would work and handle such tools which would automate those process. The governance procedures and the security control could be set as well.
6. Big Data Analytics helps in decision making and building a scalable application with Amazon Web Services would certainly help in making such decisions. At this point in time, there is still a huge amount of data that is not being used. Those unused data carries enormous information and with years to come, organizations would leave no stones unturned and would even make cloud infrastructure like AWS as the primary tool to mine those data.
For decision making, analytics is the key factor. Additionally, for strategic initiatives, big data is one of the major ingredients. In a survey conducted by the Peer-Research Big Data Analytics, it was agreed by majority that for effective business decisions, adding value to the organization, making timely analysis, big data analytics is the major factor.
7. The capability to handle various forms of data is another important feature of Amazon Web Services. Gone are those days when companies stored structured data in the form of tables in the Relational Database Management System and use SQL to perform descriptive analysis on the tabular data. These days, the maximum information is carried by data which are unstructured and generated from numerous sources across the internet.
To handle such variety of voluminous data, building scalable and robust infrastructure is a challenge and hence Amazon Web Services provides the perfect solution to that. You could easily build big data applications using both structured and unstructured data and scale those applications as well.
8. The diversity of fields or domain where big data is used is another reason why it is the best career move for you. You could apply the skills in Healthcare, Finance, Banking, Insurance, Marketing, E-Commerce and many other platforms. As most of the companies in these sectors use AWS in the backend, it would certainly improve your value if you could add big data and AWS to your skills.
9. The flexibility of the Amazon Web Services plays a major role in choosing it as one leading cloud solutions for your applications. You don’t need to pay for each and every facility but you only pay for the services you need. This makes AWS a cost-effective, robust and scalable platform for your big data problem.
10. Last but not the least and certainly one the major factors in choosing big data with AWS as the career is because of the salary that it pays and the roles that you would be working on. In India, the average package would be around 15 lakhs per annum while it is even higher outside the country such as in the UK, USA, etc.
Moreover, you would be working in roles such as Big Data Analyst, Big Data Engineer, Big Data Architect, and so on.
Going by the market trend, Big Data with AWS certainly gives you an edge over others and puts you in a better position in the market. To know more about it, you could look into Dimensionless.
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