Many companies need to make decisions based on real-time data while simultaneously needing to implement solutions quickly.
take the case of Uber, for example. Based on historical and current data, the company needs to decide peak prices, where to send drivers, which route to take, expected traffic and a whole range of data.
Thousands of such decisions need to be made every minute for a company like Uber with operations all over the world. The current flow of data and historical data must be processed to make these decisions and ensure smooth operations. These instances can use Redshift as MPP technology to streamline data access and processing.
Combining multiple data sources
There are occasions when structured, semi-structured and/or unstructured data need to be processed to gain insights. Traditional business intelligence tools do not have the ability to handle the diverse data structures from different sources. Amazon Redshift is a powerful tool in these use cases.
business intelligence
An organization's data needs to be handled by many different people. All of them are not necessarily data scientists and will not be familiar with the programming tools used by engineers.
They can count on detailed reports and information dashboards that have an easy-to-use interface.
Highly functional dashboards and automatic report creation can be created using Redshift. It can be used with tools like Amazon QuickSight as well as third-party tools created by AWS partners.
log analysis
Behavior analysis is a powerful source of useful insights. It provides information about how a user uses an app, how they interact with it, the duration of use, their clicks, sensor data, and a plethora of other data.
Data can be collected from a variety of sources — including a web application used on a desktop, mobile or tablet — and can be aggregated and analyzed to gain insights into user behavior. This union of complex datasets and compute data can be done using Redshift.
Redshift can also be used for traditional data storage. But solutions like the S3 data lake would probably be better suited for this. Redshift can be used to perform operations on data in S3 and save the output in S3 or Redshift.
The benefits of using Amazon Redshift
The most distinct advantage of using Amazon Redshift is cost-effectiveness for your organization. It only costs a fraction (approximately one-twentieth) of the cost of competitors like Teradata and Oracle.
In addition to the cost, there are several other benefits, these being the most obvious:
- Speed. With the use of MPP technology, the speed of delivering output on large data sets is unparalleled. No other cloud service provider can match the speed and cost that AWS provides.
- Data Encryption. Amazon offers data encryption capability for any part of the Redshift operation. You, as a user, can decide which operations need encryption and which operations do not.
And, as we know, data encryption provides an additional layer of security.
- family tooling. Redshift is based on PostgreSQL. All SQL queries work with it.
In addition, you can choose any SQL, ETL, and Business Intelligence (BI) tools that you are familiar with. There is no need to use the tools provided by Amazon.
- smart optimization. For a large dataset, there would be multiple ways to query data with the same parameters. Different commands will have different levels of data usage.
AWS Redshift provides tools and information to improve queries. It will also provide tips to improve the database automatically.
- Automation of repetitive tasks. Redshift has the provisions by which you can automate tasks that need to be done over and over again.
This can be administrative tasks such as generating daily, weekly or monthly reports. It could be resource and cost audit. It can also be regular maintenance tasks to clean up the data.
- simultaneous scaling. Amazon Redshift will automatically scale to support ever-increasing concurrent workloads.
- Query volume. MPP technology shines in this aspect. You can send thousands of queries to the dataset at any given time.
Still, Redshift will not slow down at all; it will dynamically allocate processing and memory resources to handle higher demand.
- AWS Integration. Redshift works well with the rest of AWS tools. You can configure the integrations between all services as per your needs and optimal configuration.
- Redshift API. Redshift has a robust API with extensive documentation. It can be used to send queries and results from bain using API tools. The API can also be used in a Python program to make coding easier.
- Security. Cloud security is handled by Amazon and the security of cloud applications must be provided by users.
Amazon provides provision for access control, data encryption, and virtual private cloud to provide an additional level of security.
- Machine Learning. Redshift uses machine learning to predict and analyze queries. This, in addition to MPP, makes Redshift perform faster than other solutions on the market.
- Easy deployment. A Redshift cluster can be deployed anywhere in the world from anywhere in minutes. You can have a high-performance storage solution at a fraction of the price set by competitors in mere minutes.
- Consistent backup. Amazon automatically backs up data on a regular basis. This can be used to restore in case of crashes, crashes or corruption. Backups are spread across different locations. Therefore, this eliminates the risk of failure of a site as a whole.
- AWS Analytics. AWS offers many analytical tools. All of these can work fine with Redshift.
Amazon supports integrating other analytics tools with Redshift. Redshift has native integration capabilities with AWS analytics services.
- open formats. Redshift supports and can provide output in many open formats for data. The most common formats supported are Apache Parquet and Optimized Row Columnar (ORC) file formats.
- Partner Ecosystem. AWS is one of the oldest cloud service providers. Many customers rely on Amazon for their infrastructure.
In addition, AWS has a strong network of partners who build third-party applications and offer implementation services. That partner ecosystem it can also be leveraged to see if you can find a perfect implementation solution for your business.
→ Also read: Implementing Amazon Redshift on Autoglass!
Summing it Up
The data collected will grow every day. That's why Redshift is a protection against growing data with increasing analytical complexity. It can be used to build an infrastructure that will last into the future.
Plus, Redshift delivers best-in-class performance at a fraction of the cost of competitors. This makes it a value proposition for any organization that needs to deal with large volumes of data.
How about, can we show you what Amazon Redshift is and how it works? talk to us right now for more details, and see how we can help you implement this solution in your company!
