There could be many challenges standing in the way of transformation. To name a few:
- The sheer size and scale of data that they handle every day. Over the next three years, there will be more data created than in the prior 30 years combined.
- Organizations need to easily access and analyze all types of data such as log files, clickstream data, voice, video, etc. This data comes from a variety of sources and is stored in silos across multiple data stores.
- Organizations need to empower their employees with secure access to data and the ability to perform analytics and machine learning on their data in an agile and cost-effective way.
- In a world of increasingly important data security, privacy, and compliance regulations, organizations need to be able to carefully define, monitor, and manage who has access to specific pieces of data through tried and tested data governance and security controls.
AWS helps organizations tackle these challenges through the Lake House approach, which brings together the best of both data lakes and purpose-built data stores. A Lake House approach supports five things:
- Allows you to build a scalable data lake rapidly
- Supports purpose-built data and machine learning services that deliver performance for your organization’s use cases
- Ensures you can move data seamlessly in, out, and around the data lake and purpose-built data services
- Maintains compliance with security, monitoring, and management of data access
- Delivers cost-effective performance and scalability
