Data is the most important asset organizations own. Without data, there would be no intelligence, insights, or analytics. The value of data lies in both its accessibility and integrity. Analytics systems harness the power of data to derive actionable insights for businesses.
As it stands, the AWS Cloud has seen strong adoption as the platform of choice for many analytics solutions. AWS dominates the cloud computing landscape with around 41.5% of the market share, more than all its competitors combined – Microsoft Azure (29.4%), Google Cloud (3.0%), and IBM (2.6%). This success is driven by the elastic scalability, cost efficiency, and security of deploying solutions in AWS. But what makes AWS the best choice for analytics initiatives? Let’s find out.
1. No Need to Worry About Scalability Issues
When running a business, it’s hard to predict how much data will be collected in the future. Businesses are often tempted to start small and add more servers as needed, but that can be expensive and time-consuming. Plus, it’s not always clear what kind of servers or storage they need at first. If the resources they deploy aren’t feasible in the long run, then they will have to go through the process of re-deploying them all over again.
With AWS, there are no worries about scalability issues because AWS hosts the business infrastructure on its high-performance infrastructure. For example, AWS-powered data lakes are highly scalable and agile. They are explicitly designed to accommodate a business’s data throughput. So, when the data lakes are built on AWS, enterprises can be assured that they’d get more profound insights than they’d otherwise extract from traditional warehouses.
Along the same lines, consider the case of Amazon Kinesis Data Firehose – an ETL service. It helps with the loading of streaming data into data stores like Amazon S3, which can then help enable real-time analytics even as the business uses its existing BI tools.
This way, even if your company is growing fast and experiencing rapid spikes in traffic, AWS can easily scale with you so that nothing gets bogged down by unexpected traffic spikes or other issues related to hosting analytics infrastructure at scale.
2. Comprehensive Range of Services and Support
The cloud offers many benefits for analytics initiatives, but AWS stands out from the crowd in its comprehensive range of services and support.
AWS’s suite of services provides users with a platform for building and deploying analytics applications and the tools they need to manage those applications once they’re in production. This includes tools for data preparation, visualization, machine learning, and more.
Users can also rely on AWS to enhance their analytics processes with industry-leading security features, including data encryption at rest and in transit, user identity management, and secure software development lifecycle (SDLC) processes.
3. Security
The security offered by AWS is unparalleled. With their advanced data encryption, enterprises can rest assured that their data is safe from prying eyes.
They can also take advantage of AWS’s multi-factor authentication and secure key management service to protect their accounts from unauthorized access. Often, businesses struggle because they cannot secure their accounts properly. So, you must consult for a service that can make this process as easy as possible.
4. Purpose-Built for Performance and Cost
The AWS platform is purpose-built for performance and cost, which means it’s the ideal solution for your analytics initiatives. It’s available on demand, so you can pay for what you use. It also offers unparalleled flexibility, allowing you to scale quickly and easily as your business grows. All of this can be attributed to the fact that AWS allows businesses to pick the tools that they deem ideal for their analytics initiatives. Here “ideal” stands for assessing the tools based on their performance, the cost they’d accrue, and the scalability they’d facilitate.
Plus, with the ability to run analytics on a global scale, no matter where your data resides, AWS offers the overall best performance and highly cost-effective cloud infrastructure for analytics initiatives.
5. Serverless
AWS’ serverless capabilities come to the fore with Amazon Redshift Serverless. In essence, Amazon Redshift, a data warehouse, powers businesses to analyze structured and unstructured data. Amazon Redshift Serverless goes a step ahead by allowing businesses to run high-performing analytics at scale. It does so by:
- Automatically provisioning the resources needed for computing
- Scaling the warehouse seamlessly as the demand/traffic increases
- Specifying the costs control options and SLAs
Such capabilities make AWS’ serverless capabilities to support even ad hoc analytics — a necessity when businesses want to rapidly test and develop applications.
6. Unified Data Access
AWS provides a unified data access solution that allows businesses to secure, manage, and analyze their data either on-premises or in the cloud. It is straightforward to implement and can be scaled from small enterprise environments to large global deployments.
The platform helps in integrating data across the enterprise and sharing it with users who need access. They can also easily move data between on-premises systems and AWS cloud services. Notably, AWS offers built-in tools for security and compliance with strict regulatory requirements.
7. Machine learning (ML) Integration
Machine learning is a key component of any analytics initiative. It helps in understanding and predicting user behavior — ultimately empowering the company to make better decisions.
However, machine learning capabilities can be challenging to implement and maintain. Companies need to make sure their machine learning model is accurate and that it’s updated as necessary.
AWS offers a suite of tools for ML integration—including Amazon SageMaker and Amazon Elasticsearch Service (Amazon ES)—to help businesses integrate ML into their existing processes and applications.
8. Mature Security Framework
AWS’s mature security framework makes it the best choice for analytics initiatives. Over the past decade, AWS has used a secure network. This means you can trust that your data will be safe and sound, even if you’re using it for sensitive purposes like handling credit card information or medical records. It also means that you don’t have to spend time configuring highly secure systems yourself.
9. Faster Results with a Fully Managed Analytic Environment
With AWS, businesses have the power of cloud analytics at their fingertips. They can get results faster with a fully managed analytics environment that automatically scales as the business grows. They can use tools like Amazon EMR and Redshift to quickly analyze data in the cloud. They can also build custom applications on these platforms to get even more out of their data.
Conclusion
AWS allows businesses to predict analytics costs, scale their initiatives as needed, and enhance the overall performance of their analytics operations. It offers a wide range of capabilities and an ever-expanding set of third-party integrations and services. By creating a seamless, frictionless foundation for data analytics, AWS positively influences the bottom line.
Interested in learning more about how AWS can complement your analytics initiatives? Get in touch with an expert today!