Top Four Ways AWS Data Lakes Accelerate Your Growth
by Rackspace Technology Staff
Businesses have always leveraged data to solve complex problems and drive growth. What’s different now is its unfathomable explosion. According to the IDC, worldwide data creation and replication are expected to grow 61% to 175 zettabytes from 2020 to 2025. With the proper planning, design, and governance, AWS data lakes can store data in any format at the petabyte scale, allowing you to access that data with your choice of analytic tools and frameworks.
The terms “data warehouse” and “data lake” are often used interchangeably, but the difference between the two is minimal. Data warehouses are optimized for relational, pre-defined structured data that operates as a source of truth for reporting and analysis tools. By contrast, a data lake stores both relational and non-relational data from various sources, allowing for the storage and querying of data with methods and tools that may not be defined yet.
While the primary goal of data lakes is to help organizations’ end users access data from different sources by storing all of it in a centralized repository, data lakes also drive organic revenue growth. For example, an Aberdeen survey saw a 9% increase for organizations that implemented data lakes. Not only were they able to do new types of analytics, like machine learning, but they were also able to make decisions and increase productivity proactively.
Here are the top four ways Onica by Rackspace Technology® uses AWS data lake accelerators to fast track digital transformation journeys on a scalable data infrastructure.
Hadoop-based on-premises data lake systems often struggle to deliver value with storage and data co-located and are challenging to integrate with other clouds and new technologies. With AWS data lakes, you can unify your data architecture, including hybrid or multi-cloud options, to achieve a complete view of your business with a seamless user experience.
Businesses in need of high-performing platforms that can efficiently and cost-effectively scale to support
modern use cases can now handle data at any scale. With AWS data lakes, you can unlock current analytics use cases, reduce the total cost of ownership and move to an operational cost model.
Currently, maintenance of existing data lake architectures consumes IT resources, capacity planning and expansion requirement times. However, you can scale your data lake governance and ecosystem expansion with AWS data lakes to support machine learning and analytics workloads with no limits.
With the ever-evolving security challenges and compliance requirements businesses face, AWS data lakes offer a way to easily maintain strong cutting-edge security practices with fine-grained identity and management controls.
Onica by Rackspace Technology provides data architecture and engineering services that accelerate your path to leveraging a highly scalable, flexible and agile AWS data lake. We’ll help you imagine the possibilities, identify use cases, and speed up your time-to-value with reference architectures and accelerators.
With 15 AWS competencies and more than 2,700 AWS certifications, we can fast track your path to becoming a truly data-driven organization. With our expertise and experience, we can deliver a proof-of-concept in just three weeks.
For more information, download the AWS Data Lake Accelerators datasheet.
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