With this course, you'll understand DynamoDB’s strengths and be aware of its pitfalls to ensure you're set up to succeed. Getting up and started quickly is very important when delivering software. DynamoDB, being a fully managed service in AWS, enables exactly this. Amazon DynamoDB is a fully managed, fast, and flexible NoSQL database service.
This course provides you with a good understanding of how the service works and the best way to leverage it while avoiding the common pitfalls. You'll learn how DynamoDB works under the covers. First, you'll explore the very basics, then move on to modelling a system in DynamoDB, to ensure it provides reliable performance and scalability. You'll gain an understanding of the capabilities DynamoDB offers, such as Triggers and learn all about Time to Live and DynamoDB Accelerator.
Finally, you’ll learn how to improve the performance and build a high-performance application database. By the end of this course, you'll understand the fundamentals of DynamoDB and be comfortable using it when building your own application.
About the Author
Colibri Digital is a technology consultancy company founded in 2015 by James and Ingrid Cross. The company works to help their clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as Big Data, Data Science, Machine Learning, and Cloud Computing.
Over the past few years, they have worked with some of the world's largest and most prestigious companies, including tier 1 investment banks, a leading management consultancy group, and one of the world's most popular soft drinks companies, helping each of them to better make sense of their data and process it in more intelligent ways.
At the frontier of AI, Big Data, and Cloud Computing, we are Colibri Digital.
James Cross is a Big Data Engineer and certified AWS Solutions Architect with a passion for data-driven applications. He’s spent the last three-five years helping his clients to design and implement huge scale streaming Big Data platforms, Cloud-based analytics stacks, and serverless architectures.
He started his professional career in Investment Banking, working with well-established technologies such as Java and SQL Server, before moving into the Big Data space. Since then he’s worked with a huge range of Big Data tools including most of the Hadoop ecosystem, Spark and many No-SQL technologies such as Cassandra, MongoDB, Redis, and DynamoDB. More recently, his focus has been on Cloud technologies and how they can be applied to data analytics, culminating in his work at Scout Solutions as CTO, and more recently with Mckinsey.
James is an AWS-certified solutions architect with several years’ experience designing and implementing solutions on this cloud platform. As CTO of Scout Solutions Ltd, he built a fully serverless set of API’s and analytics stack based around Lambda and Redshift.
