Learn how Amazon Redshift handles massive datasets and complex queries, and when it's best suited for tasks like Mortgage Portfolio Analysis or Real-Time Fraud Detection. Explore AWS QuickSight's integration with AWS data sources and its strengths in Business Intelligence and Data Exploration. Get actionable insights to make informed decisions for your projects and use cases. Watch here: youtu.be/T1cMaV8_5fQ?feature=shared

1. Amazon Redshift
and QuickSight
Simplified Guide to Cloud Data Management

2. Understanding
Amazon Redshift
Amazon Redshift is a fully managed cloud data warehouse
designed to handle petabyte-scale datasets and complex
analytic queries.
Learn about Redshift's architecture, scalability, and how it
manages Redshift Processing Units (RPUs) to deliver high-
performance data processing.
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3. 01 - REAL TIME FRAUD DETECTION
02 - MORTGATE PORTFOLIO
ANALYSIS & REPORTING
03 - REGULATORY COMPLIANCE
AND REPORTING
Amazon Redshift excels in critical fraud
prevention for mortgage applications with real-
time data analysis, seamless data stream
integration, and robust computing for
advanced fraud detection.
Financial firms rely on data for key decisions
like loan tracking and risk assessment. Amazon
Redshift's fast processing and scalability make
it ideal.
Mortgage industry compliance demands
adherence to Dodd-Frank Act, Basel III, and
similar standards. Robust reporting covers
operations, risk management, and customer
data for regulatory scrutiny.
Ideal Use Cases for Amazon Redshift
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4. 01 - HIGH-FREQUENCY
TRANSACTION PROCESSING
02 - SMALL DATA
WAREHOUSING NEEDS
03 - LOCAL STORAGE FOR
MOBILE APP
Better suited for OLTP systems like Amazon
RDS or DynamoDB, not Redshift's data
warehousing focus.
Redshift's cost may outweigh benefits for small
projects; simpler databases could be more
cost-effective.
Redshift is cloud-based, not designed for on-
device storage; use local databases like SQLite
instead.
Know When Redshift Might Not Be Ideal
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5. SETTING UP REDSHIFT
CLUSTER
Log in to AWS Console
1
Open your web browser and
navigate to the AWS Management
Console.
Log in using your AWS account
credentials.
2
3
4
5
6
Navigate to Amazon Redshift
Once logged in, locate and select the
"Amazon Redshift" service from the
AWS Console dashboard.
Create a New Cluster
In the Amazon Redshift dashboard,
click on the "Clusters" tab.
Click on the "Create Cluster" button
to initiate the cluster creation
process.
Configure Cluster Settings
Enter a unique Cluster Identifier and
Database Name for your Redshift
cluster.
Choose the appropriate Node Type
and Number of Nodes based on your
workload requirements.
Set Up Cluster Permissions
Define the Master User Name and
Password for accessing the Redshift
cluster.
Configure the VPC (Virtual Private
Cloud) settings and Security Groups
to control network access.
Launch Cluster
Review all the configuration settings
to ensure they meet your
requirements. Once satisfied, click
the "Create Cluster". The cluster
creation process may take several
minutes to complete.
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6. Exploring AWS
QuickSight
AWS QuickSight is a fully managed business intelligence (BI)
service that integrates seamlessly with AWS data sources.
Discover how QuickSight enables visualizing data from sources
like S3, Redshift, and RDS, making data analysis accessible and
insightful.
https://www.aptuz.com/

7. 01 - BUSINESS INTELLIGENCE
AND REPORTING
02 - INTEGRATING AWS
DATA SOURCES
03 - NON-TECHNICAL USER
DATA EXPLORATION
Ideal for businesses needing interactive data
visualization and business intelligence
capabilities.
Well-suited for organizations heavily invested
in AWS ecosystem, looking to analyze data
from AWS services seamlessly.
Great for users without deep technical
expertise needing to explore data and generate
insights.
Ideal Use Cases for AWS QuickSight
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8. 01 - COMPLEX, CUSTOMIZED
DATA ANALYSIS
02 - LARGE-SCALE MACHINE
LEARNING INTEGRATION
03 - NON-AWS DATA INTEGRATION
It is not the best choice for highly specialized
analytical needs requiring extensive
customization.
Limited capabilities for advanced machine
learning and predictive analytics compared to
specialized tools.
Less ideal for businesses primarily using non-
AWS data sources or requiring extensive
integrations outside the AWS ecosystem.
Considerations for AWS QuickSight
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9. THANK YOU
https://www.aptuz.com/

10. CONTACT US
https://www.aptuz.com/
info@aptuz.com
4th Floor, RAM SVR, Madhapur,
HITEC City, Hyderabad -
500081
+(91)-9491754728
https://www.aptuz.com/