Career Range of Data Science and AWS
                     Career Range of Data Science
 and AWS
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As technological advancements make our life much more 
comfortable, the increasing dependency of people on technology 
has given rise to more career options in the IT industry. Earlier, 
people had limited career platforms, but today data reinforces all 
the revolutionary technologies. From Social media to IoT devices, 
data has been like a golden goose lately. Organizations these 
days are so dependent on data that it acts as a fuel in their 
growth. But is data enough to escalate a business? Indeed 
knowing the effective use of data to draw useful insights from it 
is a crucial factor. This is where Data Science comes into play. 
Data Science is a method of utilizing data to determine solutions 
to foresee consequences for a problem statement.
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Also, Cloud Computing is a favored career choice these days. AWS being flexible is the most 
common reason it is preferred as a career platform by many IT professionals. This flexibility 
translates directly into affordability as Cloud computing does not require expensive hardware, 
specialty software implementation, or maintenance. With many more clients moving to the 
AWS cloud, there has been a surge in the interest of proficient individuals who comprehend 
the intricate details of cloud computing and its application and management.
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Data Science
Data Science is a process of extracting understanding and comprehension from an 
accumulation of structured and unstructured data using scientific methods and 
algorithms. It involves the below steps:
1. Business Requirements:A data science process always commences with 
learning the business requirement or the problem you are trying to solve. One needs 
to understand and define the objectives of the intricacy that needs to be undertaken. 
To become an accomplished Data Scientist, you must be a curious soul and possess 
an inquisitive trait.
2. Data Acquisition: Entertaining business requirements are ordinarily 
accompanied by data collection and analysis. You need to gather and abrade data 
from various references like web servers, logs, databases, APIs, and online 
repositories. In order to find profitable data, you need to invest both time and effort.
3. Data Preparation: This step incorporates Data Cleaning and Data 
Transformation. It is often possible that while data acquisition, some unnecessary 
data is collected that can increase the complexity of the problem. Data cleaning 
involves many complex scenarios, so it is a time-consuming process. You will have to 
deal with inconsistent datatypes, misspelled attributes, missing or identical values. 
Data transformation involves modifying and altering the data based on some 
predefined mapping rules. You need to perform complex transformations to improve 
the data structure.
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4. Exploratory Data Analysis: It is very crucial to determine how you can utilize 
the data in an efficient way. This is a very important step that is like the brainstorming of 
data analysis, where you understand the patterns in your data. One needs to define and 
refine the selection of feature variables that will be used in model development.
5. Data Modelling: This is a core activity of a data science project, which includes 
building a machine learning model built using all the insights and trends collected in 
the previous step. One needs to apply varied techniques in order to identify the best-
suited model as per the business requirements.
6. Data Validation: In this step, the entire data is reviewed for anomalies and 
false predictions. If any anomalies are detected, a notification is sent to the respective 
data scientist who will fix the problem. Powerful reports and dashboards are created at 
this step.
7. Deployment and Maintenance: This is the final step in a data science 
project where the data is tested in a pre-production environment before it is deployed 
in the production environment. It is further monitored and maintained as per its 
performance.
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AWS
AWS, an abbreviation of Amazon Web Services, is a cloud service provider that 
offers on-demand cloud computing platforms to individuals, companies, and 
governments. It was launched in 2006 but is the most popular and used Cloud 
Computing Platform. It has acquired a significant share in the market, so its 
certifications are in high demand. Many prominent companies use AWS 
infrastructure for their Cloud Computing needs. It is needless to say that AWS 
certification is the game changer of your career.
It entirely dominates the Cloud Computing domain by leading the market. It 
offers a broad spectrum of services for many domains. A lot of tech giants have 
shown their trust in AWS for fulfilling their Cloud computing requirements. AWS 
has many years of experience in the Cloud Computing domain and has created 
trust among its customers.
Around 90% of companies are making use of Cloud technology these days. The 
development of Cloud Computing is outperforming the growth of the entire IT 
area. This is obviously the surge of what might be in the future.
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Data Science with AWS
As Data Scientist is anything but simple work, the security is ensured, and the 
work includes analyzing programming and business aptitudes to handle gigantic 
measure of sensitive data. This needs security, infrastructure, and power for 
productive and secured working that is provided by AWS. There are numerous 
advantages if the two professions are blended, for example:
• Give admittance to pre-introduced source applications
• Security and data research
• Handling and storage of data
• Financially savvy
• A better and improved approach to deal with the organization culture
As both of the vocations convey a significant job in handling the data, both carry 
a wide scope regarding building a profession in one. Experts who are enjoying 
both are getting a lot more significant compensation and astonishing open doors 
from fortune 500 organizations from India and abroad.
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Conclusion
Be it AWS or Data Science, people are game at the moment. It completely 
depends on the area of your interest because both the career platforms are 
booming in the market. In today’s competitive world, having active Cloud 
services involvement like AWS gives a significant advantage in the Data Science 
race. AWS at present is exceptionally well known among organizations, and your 
experience with such cloud computing platforms features your aptitudes during 
the recruitment process.
AWS with Infosec Train
You can opt for any AWS training from Infosec Train for professional knowledge 
and an in-depth understanding of Cloud technology. We are among the leading 
training providers worldwide, with our well-versed and experienced trainers. The 
courses will help you understand the basic concepts and provide a sound 
knowledge of the subject. This certification will indeed merit each penny and 
minute you have invested.
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About InfosecTrain
• Established in 2016, we are one of the finest 
Security and Technology Training and 
Consulting company
• Wide range of professional training programs, 
certifications & consulting services in the IT 
and Cyber Security domain
• High-quality technical services, certifications 
or customized training programs curated with 
professionals of over 15 years of combined 
experience in the domain
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