Big Data on Amazon web services (AWS)
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Big Data on Amazon web services (AWS)

Big Data on Amazon web services (AWS)

Big Data on Amazon web services (AWS)


Learn About Building out Scalable, Resilient Big Data Solutions Using Various Services on AWS Cloud Platform

- You will be able to understand the possibilities of Big Data on AWS
- You will gain practical experience of how to use AWS and how to perform big data solutions on cloud.
- Get a fair understanding of EMR,Athena and Elasticsearch

This Big Data on AWS course is primarily to simplify the use of Big data tools on AWS. With the unstoppable growth in the organizations moving towards data science and big data analytics there is a dearth need of trained professionals who are well versed with both Big data and AWS technologies. This course helps the learners get the best of both worlds (Big Data analytics and AWS Cloud)  and prepare for the future.   

We cover the following topics in this course:

- Overview of Big Data on AWS
- Big Data Storage  & databases on AWS
- Big Data Analytics Frameworks using AWS EMR, Athena and Elasticsearch
- Data Warehousing on AWS Redshift
- Real-Time Big Data Analytics on AWS
- Artificial Intelligence/Machine Learning
- Business Intelligence on AWS
- Big Data Computation on AWS
- How does it all work together

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Whether you’re interested in specific functions of Amazon AWS, like creating APIs, or more broad introductions to both implementing AWS and becoming a certified AWS Architect, Nixon has a course to help you achieve your goals.

Learn more about Amazon AWS

Amazon Web Services is cloud computing platform that facilitates scalability and growth within organizations through a suite of databasing, storage, and computing tools. Specifically, AWS enables teams to leverage data-driven infrastructure services to create intuitive and flexible cutting-edge applications.

What is Amazon Web Services (AWS)?

Amazon Web Services is a leading cloud platform that offers users over 200 comprehensive services from secure global data centers. Its creators engineered this cloud platform for high flexibility and security in the cloud computing environment. The core infrastructure meets the rigorous security requirements for global banks, the military, and other organizations needing maximum protection. 

The cloud security tools integrate 230 security compliance features to ensure data protection. Data encryption is available within all the AWS services. AWS offers a vast array of databases that are purpose-built, so users maximize efficiency and cost-effectiveness with the right tool to get the job done. Users benefit from innovative features like storage, databases, computing, machine learning, data analysis, artificial intelligence, and advanced connectivity with the Internet of Things.

Who uses AWS?

Amazon Web Services has millions of active global customers from a wide variety of industries who are using this cloud platform to build, implement, and host applications. Some of those industries include banking, non-profit, media, manufacturing, and government. These customers range from individual entrepreneurs and startups to businesses of every size and all types of public sector organizations. 

However, the majority of their base customers are smaller to mid-size businesses. AWS offers the AWS Partner Network (APN) to technology systems integrators to utilize this cloud platform to create optimized cloud technology solutions for their customers. Independent software vendors (ISVs) have modified their technology solutions for compatibility on AWS.

Does AWS require programming skills?

Coding skills are not required to work with Amazon Web Services. Users can easily perform most basic tasks without having any coding background. Most new users utilize the AWS UI to create their infrastructure rather than using coding tools. The UI approach is the most streamlined way to use AWS. However, for more professional uses, it is important to learn manual code configuration. 

If you want to excel in AWS, knowledge of Linux Scripting and Programming languages will improve the learning process. If you want to be an AWS developer, you need programming knowledge in varying languages. You must have experience in cloud computing, networking, and AWS Lambda, their serverless computing space. Cultivating specific technical skills will help you succeed as an AWS developer.

What are the certifications I can get with AWS?

You can gain six months of foundational AWS Cloud and industry knowledge when you get a certification as an AWS Certified Cloud Practitioner. Three associate certifications can give you one year of experience in resolving issues and integrating solutions using the AWS Cloud. These are AWS Certified Solutions Architect, AWS Certified Developer, and AWS Certified SysOps Administrator. 

There are two professional certifications that provide two years of experience in creating, running, and troubleshooting solutions with the AWS Cloud. Those certifications are AWS Certified Solutions Architect and AWS Certified DevOps Engineer. Six specialty certifications are available to help you gain technical AWS Cloud experience in specialty domains. Those are AWS Certified Advanced Networking, AWS Certified Data Analytics, AWS Certified Security, AWS Certified Machine Learning and more.

What are the AWS core services?

AWS core services are AWS Compute, AWS Storage, AWS Database, AWS Networking, AWS Management, AWS Security, and AWS Application Integration. The EC2 service enables streamlined scalability for virtual machines. Simple Storage Services (S3) are object-based for cloud storage. On-demand scalability and blazing performance are available with the DynamoDB NoSQL database option. 

In-memory caches are created with ElastiCache. The Virtual Private Cloud (VPC) is provided for routing tables, gateways, subsets, and security mechanisms. Key services can be monitored through CloudWatch, and cloud databases can be hosted with the Relational Database Service (RDS). API calls to AWS are tracked by CloudTrail. Users, groups, and roles can be created with Identity and Access Management (IAM) service.

What is serverless architecture?

Serverless architecture has a software design blueprint with third-party hosting for applications. This is known as serverless computing of function as a service (FaaS). This innovative serverless architecture removes the need for server software and developer management of hardware. Three key benefits of serverless architecture are decreased costs since you only pay for what you use, increased developer productivity, and improved scalability. 

With FaaS, applications are broken down into smaller sections to enhance the observation process. AWS is continually experimenting and innovating its services. As a pioneer in the cloud computing industry, AWS launched AWS Lambda, the serverless computing space, in 2014. This innovative technology enabled code operation without having to provision or manage servers. 

AWS vs. Microsoft Azure vs. Google Cloud Platform (GCP)?

Amazon Web Services holds the lead position of these platforms, with Microsoft Azure ranked second and Google Cloud Platform ranked third. AWS offers a vast array of tools and continues to grow exponentially through innovation. However, they offer a complex price structure and are focused more on a public cloud platform than private cloud or hybrid cloud options. 

Microsoft Azure has more substantial Software-as-a-Service (SaaS) capabilities compared to AWS and Google Cloud. Google has been an innovator in artificial intelligence, machine learning, deep learning, and data analytics for some time. This continual innovation has enabled them to effectively integrate AI into their cloud platform. They have also provided customers with more discount incentives than the other two platforms.

Requirements

- This course does not presume that students have prior knowledge of AWS or its Big Data services.
- Having a fair understanding of Java and SQL would help but it is not mandatory.

Who this course is for:

- Big data aspirants
- AWS enthusiasts
- Software Developers and Architects
- Analytics Professionals
- Senior IT professionals
- Testing and Mainframe Professionals
- Data Management Professionals
- Business Intelligence Professionals
- Project Managers
- Aspiring Data Scientists
- Graduates looking to build a career in Big Data Analytics

Big Data on Amazon web services (AWS)
Big Data on Amazon web services (AWS)

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