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CoursesAWSAWS Certified Data Analytics – Specialty

AWS

AWS Certified Data Analytics – Specialty

The AWS Certified Data Analytics – Specialty course shows that you know how to design, build, and secure analytics solutions on AWS. It includes using services like Redshift, S3, Glue, Athena, and QuickSight to collect, store, process, and display data.

5/5(4,890 Reviews)

Level

Advanced

Duration

8 weeks

What is AWS Certified Data Analytics – Specialty?

The AWS Certified Data Analytics – Specialty course is for people who work in data analytics and want to learn how to use AWS for more advanced tasks.It is all about making data solutions that are safe, can grow, and don't cost too much.Using AWS services, you will learn how to collect, store, process, and visualize data.This certification shows that you can turn raw data into useful information that can help a business grow.

Training Plan

About trainer

Working professional who is carrying more then 10 years of industry experience.

Decks

The candidate will get access to the presentation taken-up during the session.

Notes

Consolidated notes in word document.

Assignments

Assignments for every module will be covered.

MCQs

MCQs for every module covered in the session would be provided.

Video Recording

Daily Session would be recorded and shared to the candidate.

Dumps for Certification

We will provide dumps for the certification exam, which will help you to prepare for the exam.

Updated Content

We provide Generative AI Driven content By experts.

Projects

3 Live Projects will be provided for practice.

AWS Certified Data Analytics – Specialty Course Curriculum

Introduction to AWS Data Analytics

Section 1

Understand the exam scope, AWS analytics services, and use cases.

Exam domains overview

Analytics service categories

AWS data lifecycle

Use cases & architecture patterns

Data Collection

Section 2

Learn to ingest structured and unstructured data at scale.

Kinesis Data Streams

Kinesis Data Firehose

AWS IoT Core ingestion

Database migration service (DMS)

Data Storage & Management

Section 3

Explore storage solutions optimized for analytics workloads.

Amazon S3 data lake

Redshift data warehouse

DynamoDB for NoSQL storage

AWS Glue Data Catalog

Data Processing & Transformation

Section 4

Transform, clean, and prepare data for analysis.

AWS Glue ETL jobs

Amazon EMR (Spark/Hadoop)

AWS Lambda for stream processing

Data pipelines orchestration

Data Analysis & Query Services

Section 5

Query and analyze data using AWS managed services.

Amazon Athena (serverless SQL)

Amazon Redshift Spectrum

Kinesis Data Analytics

Federated queries

Data Visualization & Reporting

Section 6

Present insights using visualization tools and dashboards.

Amazon QuickSight

BI dashboards & reporting

Storytelling with data

Integrating ML insights

Security in Data Analytics

Section 7

Apply governance, compliance, and data security best practices.

IAM roles & fine-grained access

KMS encryption at rest & transit

Lake Formation security policies

Data governance frameworks

Monitoring & Optimization

Section 8

Monitor, troubleshoot, and optimize analytics workloads.

CloudWatch monitoring

Logging & auditing with CloudTrail

Cost optimization strategies

Query & performance tuning

Machine Learning Integration in Analytics

Section 9

Use AWS ML services to enhance data analytics solutions.

Amazon SageMaker integration

ML models with Redshift ML

Forecasting with AWS Forecast

Personalized insights with Personalize

Exam Preparation & Case Studies

Section 10

Strengthen exam readiness with scenarios and practice.

Hands-on labs & sample datasets

Case study walkthroughs

Practice test questions

Best practices & common pitfalls

Key Projects

AWS Certified Data Analytics – Specialty

Real-Time Streaming Analytics with Kinesis

Create a real-time data pipeline with Amazon Kinesis to record live streams (such as clickstream or Internet of Things data), process them using AWS Lambda or Kinesis Data Analytics, store the raw data in S3, and then import the processed output into Redshift. Lastly, build QuickSight dashboards to see real-time trends such as fraud detection, sensor monitoring, and user activity.

Data Lake with ETL Pipeline

Create a centralized data lake on Amazon S3 to house both structured and unstructured data from RDS, DynamoDB, and Kinesis, among other sources. For ETL and schema discovery, use AWS Glue; for data querying, use Athena; and for data security, use IAM and KMS. QuickSight provides analysts with direct access to and visualization of data for reporting and insights.

Business Intelligence Dashboard with Redshift

To make a BI solution, get sales and customer data from RDS, change it with Glue, and then load it into Redshift so that it can be queried more easily. Use Step Functions to create automated pipelines and QuickSight dashboards to help businesses keep track of key performance indicators (KPIs) like revenue, retention, and product performance.

AWS Certified Data Analytics – Specialty – Associate Training Program

Name: AWS Certified Data Analytics – Specialty
Rating: 5.0 (4890 reviews)

Category

Associate

Exam Name:

AWS Certified Data Analytics – Specialty – Associate

Exam Code:

N.A.

Exam Duration:

N.A.

Exam Format:

N.A.

Passing Score:

N.A.

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Frequently Asked Questions (FAQs)

What is the AWS Certified Data Analytics – Specialty certification?

This certification validates expertise in designing, building, and maintaining analytics solutions on AWS. It focuses on collecting, storing, processing, and visualizing data efficiently. Techpratham explains that it demonstrates strong skills in cloud-based data analytics pipelines.

Who should take the DAS-C01 exam?

The exam is intended for data analysts, data engineers, and business intelligence professionals working with AWS analytics services. It suits candidates responsible for big data solutions and insights generation. Techpratham highlights that it’s ideal for cloud professionals handling analytics workflows.

What skills are measured in DAS-C01?

The exam measures data collection, storage, processing, visualization, security, and cost optimization. It also tests knowledge of AWS services like Redshift, Kinesis, Athena, Glue, and QuickSight. Techpratham notes that understanding ETL processes and query optimization is critical.

Are there prerequisites for DAS-C01?

There are no strict prerequisites, but AWS recommends 5+ years of experience in data analytics and 2+ years on AWS. Familiarity with databases, data lakes, and visualization tools is helpful. Techpratham suggests hands-on practice with AWS analytics services before attempting the exam.

How long is the DAS-C01 certification valid?

The certification is valid for 3 years, after which recertification is required. Techpratham emphasizes keeping up with new AWS analytics services and best practices to stay current.

How much does the DAS-C01 exam cost?

The exam costs $300 USD, reflecting its specialty-level nature. Techpratham advises budgeting for both the exam and hands-on practice resources.

What is the format of the DAS-C01 exam?

The exam includes multiple-choice and multiple-response scenario-based questions. It tests practical ability to design and implement analytics solutions. Techpratham explains that scenario-based questions simulate real-world data analytics challenges.

How should I prepare for the DAS-C01 exam?

Preparation includes AWS training, hands-on labs, sample datasets, and study of analytics workflows. Focus on Redshift, Glue, Kinesis, Athena, and QuickSight. Techpratham recommends building end-to-end analytics pipelines to reinforce practical knowledge.

What job roles can I get after earning DAS-C01?

The certification qualifies candidates for roles like Data Engineer, Data Analyst, BI Developer, and Cloud Analytics Specialist. Techpratham notes that it’s highly valued in organizations leveraging AWS for large-scale data solutions.

Is the DAS-C01 exam considered difficult?

Yes, it is challenging due to its focus on both technical AWS services and data analytics concepts. Techpratham stresses that hands-on experience and practice with real datasets are key to passing the exam.Is the DAS-C01 exam considered difficult? Yes, it is challenging due to its focus on both technical AWS services and data analytics concepts. Techpratham stresses that hands-on experience and practice with real datasets are key to passing the exam.

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