AWS Redshift tutorial

2. Amazon Redshift is a data warehouse product which forms part of the
larger cloud-computing platform Amazon Web Services. It is built on top of
technology from the massive parallel processing (MPP) data warehouse
company ParAccel (later acquired by Actian), to handle large scale data
sets and database migrations.Redshift differs from Amazon's other hosted
database offering, Amazon RDS, in its ability to handle analytic workloads on big
data data sets stored by a column-oriented DBMS principle. Redshift allows up to
16 petabytes of data on a cluster compared to Amazon RDS Aurora's maximum
size of 128 terabytes.
Amazon Redshift is based on an older version of PostgreSQL 8.0.2, and Redshift
has made changes to that version. An initial preview beta was released in
November 2012 and a full release was made available on February 15, 2013. The
service can handle connections from most other applications
using ODBC and JDBC connections. According to Cloud Data Warehouse report
published by Forrester in Q4 2018, Amazon Redshift has the largest number of
Cloud data warehouse deployments, with more than 6,500 deployments.

3. Redshift uses parallel-processing and compression to decrease
command execution time. This allows Redshift to perform operations on
billions of rows at once. This also makes Redshift useful for storing and
analyzing large quantities of data from logs or live feeds through a
source such as Amazon Kinesis Data Firehose.
Tens of thousands of customers today rely on Amazon Redshift to
analyze exabytes of data and run complex analytical queries, making it a
widely used cloud data warehouse. Run and scale analytics in seconds
on all your data without having to manage your data warehouse
infrastructure.

4. Why we need Redshift?
Amazon Redshift seemed like a solution for our problems of disk space
and performance. It is a columnar database which is a fully managed,
scalable, fast, and cost-effective data warehouse solution. Amazon
Redshift’s columnar data storage, massively parallel processing (MPP)
and efficient integration with other AWS services provided a very reliable
and effective solution to business intelligence and analytics platform.

5. Use Case for Redshift
Improve financial and demand forecasts
Automatically create, train, and deploy machine learning models for
predictive insights.
Collaborate and share data
Securely share data among accounts, organizations, and partners while
building applications on top of third-party data.

6. Use Case for Redshift
Optimize your business intelligence
Build insight-driven reports and dashboards using Amazon QuickSight,
Tableau, Microsoft PowerBI, or other business intelligence tools.
Increase developer productivity
Get simplified data access, ingest, and egress from numerous
programming languages and platforms without configuring drivers and
managing database connections.

7. Amazon Redshift uses SQL to analyze structured and semi-structured
data across data warehouses, operational databases, and data lakes,
using AWS-designed hardware and machine learning to deliver the best
price performance at any scale.

8. Did you know that you can get Amazon Redshift for free? If you are new
to Redshift (i.e. you’ve never created an Amazon Redshift cluster) you’re
eligible for a two-month free trial.
What is included?
•A dc1.large server with 2 CPU, 15 GB Ram, and 160 GB SSD storage
•Amazon will give you 750 hours each month, for two months
This is a perfect solution to experiment with new analytic tools, kickstart a
project or a proof-of-concept initiative. It is also a great way for you to get
an enterprise-class data warehouse with little investment.

9. Benefits of Redshift
•Optimized for Data Warehousing: Amazon Redshift has a massively
parallel processing (MPP) data warehouse architecture, parallelizing and
distributing SQL operations to take advantage of all available resources.
•Encryption: With just a couple of parameter settings, you can set up
Amazon Redshift to use SSL to secure data in transit and hardware-
accelerated AES-256 encryption for data at rest.
•Petabyte Scale: With a few clicks in console or a simple API call, you
can easily change the number or type of nodes in your data
warehouse and scale up all the way to a petabyte or more of compressed
user data.

10. Benefits of Redshift
•Query your Amazon S3 “data lake”: Redshift Spectrum enables you to
run queries against exabytes of unstructured data in Amazon S3, with no
loading or ETL required.
•Fault Tolerant: Amazon Redshift has multiple features that enhance the
reliability of your data warehouse cluster.
•Automated Backups: Amazon Redshift automatically and continuously
backs up new data to Amazon S3.

11. THANK YOU
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