- Data Lake
To keep pace with the dynamic business landscape, organizations need to respond quickly and effectively with easy access to data – cloud platforms with low-cost data storage offerings like data lakes and a plethora of powerful analytical tools are a key enabler. To maximize business value, self-service data needs and usage scenarios must also be considered.
As enterprise organizations shape strategies around data lakes, data democratization, and self-service, it is vital to consider how these data lake platforms can be designed to be agile and flexible, with appropriate governance, and meet the self-service reporting and analytical needs of an organization. Some of the common considerations include balancing process and control with the agility and flexibility that users desire, the ability to quickly ingest new data assets particularly for experimentation and analytical needs, and enabling easy and wide access to data assets.
In this webcast, we will share our thoughts on some of the key considerations in designing an agile and responsive data lake with just-enough controls to successfully deliver to self-service needs. We will discuss how automation can be introduced to increase accessibility of the data lake to a broad spectrum of users, with varying degree of skills, whilst ensuring governance and responsible usage.
What to expect
Drawing from our experience working with customers on data lake strategies and implementations, we will:
- Explore the importance of catering to self-service reporting and analytical needs with a data lake, and strategies to achieve this
- Discuss common self-service usage patterns as well as potential pain points and challenges that may be encountered
- Discuss and demonstrate approaches to make data lakes more accessible to all type of users
Is it for you?
- Are you exploring approaches to effectively use a data lake for self-service and democratize data for consumption?
- Are you looking to expand the usage of your data lake and empower your user community?
- Have you begun designing or implementing data lakes?