AWS Data Analytics Fundamentals Course Overview


AWS Data Analytics Fundamentals is a course designed to provide students with a fundamental understanding of the core technologies and services available on the AWS cloud. This course provides an in-depth overview of the AWS Data Analytics platform, the different components of the entire cloud-based analytics stack, and important concepts related to data collection, storage, and analysis.
In this course, students receive hands-on training to analyze data sets and create visualizations on the AWS platform. They learn how to use Amazon Simple Storage Service (S3) as a data repository, as well as how to use Amazon Athena to query data stored in S3. They also explore Amazon Kinesis and Amazon Redshift for streaming data and data warehouse analysis. Finally, using Amazon QuickSight, students learn how to create interactive visualizations for insights and decision making.
AWS Data Analytics Fundamentals is designed for data analysts, data scientists, business intelligence professionals, architects, cloud engineers, and IT leaders who want to acquire the skills to leverage the AWS Data Analytics platform for their organization.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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The 1-on-1 Advantage

Get 1on-1 session with our expert trainers at a date & time of your convenience.
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Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.
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Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Introduction to data analysis solutions
  • Data analytics and data analysis concepts
  • Introduction to the challenges of data analytics
  • Introduction to Amazon S3
  • Introduction to data lakes
  • Introduction to data storage methods
  • Introduction to data processing methods
  • Introduction to batch data processing
  • Introduction to stream data processing
  • Introduction to source data storage
  • Introduction to structured data stores
  • Introduction to semi-structured and unstructured data stores
  • Understanding data integrity
  • Understanding database consistency
  • Introduction to the ETL process
  • Introduction to analyzing data
  • Introduction to visualizing data
  • Putting the pieces together
  • What’s next
Live Online Training (Duration : 8 Hours) Fee On Request
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
AWS Customer Obsession Award in August 2022.
winner of the AWS Training Partner of the Year Award – APJ Region for 2022. The award was given in a glittering ceremony in Las Vegas attended by Subo
Course Prerequisites

No prior knowledge or experience is required for taking AWS Data Analytics Fundamentals Training. However, basic knowledge of AWS and its services will be helpful.

Target Audience


The AWS Data Analytics Fundamentals training is designed for a diverse audience, including data architects, data engineers, database administrators, data analysts, product managers, business analysts, business intelligence analysts, and developers who want to understand and use the analytics services provided by AWS
The training is also beneficial for anyone who wants to develop an understanding of the core principles in data analytics along with the various AWS services that can be used to extract and analyze data
No prior experience with analytics or AWS is necessary
With the AWS Data Analytics Fundamentals training, participants are guided through an exemplar end-to-end analytics solution to see what it takes to build a data lake, data warehouse and data lakehouse solution on AWS

Learning Objectives of AWS Data Analytics Fundamentals


This course will teach learners the fundamental concepts and techniques needed to analyze data using AWS services. Objectives include understanding the principles of data analytics and the basics of AWS services like Amazon EMR, Amazon S3, and Amazon Athena. Learners will also become familiar with Big Data frameworks such as Spark and Hadoop, as well as visualize the data using popular tools like Amazon QuickSight and Tableau. Finally, participants will learn how to operationalize their data analysis projects and find ways to optimize and scale their results. By the end of this course, learners will be able to confidently create and deploy highly efficient data analytic solutions using their understanding of AWS cloud-based services.

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FAQ's


Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
Yes, you can pay from the course page and flexi page.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
Yes, we do. For details go to flexi
Yes, the site is secure by utilizing Secure Sockets Layer (SSL) Technology. SSL technology enables the encryption of sensitive information during online transactions. We use the highest assurance SSL/TLS certificate, which ensures that no unauthorized person can get to your sensitive payment data over the web.
We use the best standards in Internet security. Any data retained is not shared with third parties.
1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, we also offer weekend classes.
Yes, we do offer corporate training More details
We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the digital certificate post training completion via learning enhancement tool after registration.
Yes you can.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our @koenig-solutions.com email address.
You can pay through debit/credit card or bank wire transfer.
Yes you can request your customer experience manager for the same.
Credit card transactions normally take 48 hours to settle. Approval is given right away; however,it takes 48 hours for the money to be moved.
Yes, we do accept partial payments, you may use one payment method for part of the transaction and another payment method for other parts of the transaction.
Yes, if we have an office in your city.
Yes, we do.
You can request a refund if you do not wish to enroll in the course.
To receive an acknowledgment of your online payment, you should have a valid email address. At the point when you enter your name, Visa, and other data, you have the option of entering your email address. Would it be a good idea for you to decide to enter your email address, confirmation of your payment will be emailed to you.
After you submit your payment, you will land on the payment confirmation screen.It contains your payment confirmation message. You will likewise get a confirmation email after your transaction is submitted.
Yes, fee excludes local taxes.
Yes, we do.
The Fee includes:
  • Testing Via Qubits
Yes, Koenig Solutions is a AWS Learning Partner
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.

Prices & Payments

Yes, We are
Yes of course.

Travel and Visa

Yes we do after your registration for course.

Food and Beverages

Yes.

Others

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