Building Your Data Lake on AWS
The following is a guest post from Ken Chestnut, Global Ecosystem Lead, Big Data, AWS
In my opinion, there’s never been a better time to take advantage of data and analytics. With people, businesses, and things, moving online and getting instrumented, organizations have an unprecedented opportunity to discover new insights and deliver business results. However, with this opportunity comes complexity and traditional data management tools and techniques aren’t enough to fully realize the potential of data.
Why? Because data has traditionally been stored and managed in relational databases, organizations have, in the past, had to predetermine which questions they wanted answered and force data into columns and rows, accordingly. With traditional storage and compute options historically being expensive, organizations were further constrained by the amount of data they could afford to analyze.
With greater agility, affordability, and an ability to decouple storage and compute, more organizations are turning to the cloud and using Data Lakes as a different approach to manage and analyze data. By using a Data Lake, organizations no longer need to worry about structuring or transforming data before storing it and can rapidly analyze data, to quickly discover new business insights.
To discuss the benefits of architecting a Data Lake on AWS, tomorrow (Nov. 3rd) we are hosting a webinar with three of our AWS Big Data Competency Consulting Partners: 47Lining, Cloudwick, and NorthBay.
In this webinar, these partners will share their customer success and best practices for implementing a Data Lake on AWS. You can register here.
47Lining was chosen by Howard Hughes Corporation to develop a Managed Enterprise Data Lake based on Amazon S3 to fuse on-premises and 3rd party data in order to enable them to answer their most interesting business questions. You can learn more about how 47Lining helped Howard Hughes and how they can help your organization rapidly uncover new business insights by downloading the company’s eBook here.
When a major healthcare company needed an AWS-based Big Data solution that enabled them to ingest data quicker and leverage near real-time analytics, they chose Cloudwick to architect a Data Lake on AWS. To learn more about how Cloudwick helped this organization and can help yours, read the company’s eBook here.
NorthBay helped Eliza Corporation architect a Data Lake on AWS that enabled them to manage an ever-increasing volume and variety of data while maintaining HIPAA compliance. Download the company’s eBook here to learn more about how NorthBay helped Eliza obfuscate protected data and how they can help you solve your most complex big data challenges. You can learn more about how Eliza Corporation moved healthcare data to the cloud here.
Learn about all of our AWS Big Data Competency Partners by visiting us here.
Please contact us at firstname.lastname@example.org with any questions, comments, or feedback.
We look forward to seeing you tomorrow.
UPDATE, 11/11 – Watch the webinar on-demand: