In today’s world of data proliferation, data-driven companies want to aggregate disparate data sets so that they can get the most value from them. Many companies like yours are migrating data to Hadoop data lakes in the cloud as a logical approach providing scalability and affordability. Some are finding that integrating and ingesting data from various, heterogeneous platforms into data lakes can be a complex undertaking, especially when real-time data is a requirement.
Recently, we ran a webinar featuring Noel Yuhanna, Principal Analyst at Forrester, presenting the latest trends, challenges – including data latency, heterogeneity, and data security – and best practices for building a Hadoop data lake in the cloud. Noel was joined by subject matter experts from MapR and Attunity who discussed technologies that solve these challenges and highlight customers who are building Hadoop data lakes in the cloud today.
According to Noel, organizations are leveraging a data lake in the cloud for:
- 360-degree view of the customer, business, and product
- IoT analytics
- Self-service data marts
- Cyber-security analytics
- Archiving – analytics, compliance, historical data
- Various vertical analytics and predictive analytics
- DevOps and test environments
- And more
He went on to say that when a data lake on the cloud is part of your corporate strategy you can:
- Accelerate big data deployment for Faster time to value
- Help integrate data quickly across silos – especially data that is born in the cloud
- Lower costs – 20% or more over on-premises solutions
- Enjoy Automated provisioning, scalable, high available, requires less people effort, setup time, upgrades
- Get security – in some cases is better than on-premises
- Leverage new features that are rolling in the cloud-first strategy
To learn more, watch the on-demand webinar “Best Practices for Building a Hadoop Data Lake in the Cloud”.