A common question that organizations looking to adopt a big data strategy struggle with is - which solution might be a better fit, Hadoop vs. Spark, or both? To help answer that question, here’s a com

Raman Narasimhan underlines four key aspects to consider in the current climate from a data lake and analytics perspective.

Zeotap saw a 10x growth with the number of data pipelines and amount of data processed growing at rapid pace in a short span of time. The increasing scale challenged our capability to track production

Debugging slow spark applications when done with trial and error, takes lots of time. Sparklens provides insights about scalability limits of spark applications from a single run of the application. I

Presto revolutionized the data lake. This smart query engine enables organizations to quickly adopt an effective data lake architecture that supports a wide range of workloads and use cases. But ever

Data environments are complex, but your data technology stack doesn’t have to be. Advances in data lake and analytics technologies now allow data teams to simplify their data stack, reducing unnecessa

Ever had your CEO look at a report and say the numbers look way off? Has a customer ever called out incorrect data in one of your product dashboards? If this sounds familiar, data reliability should b

Presented by Srikanth Venkat, Privacera. Enterprises migrating to the cloud for increased agility and elasticity is the new reality. As such, the migration of analytic workloads from on-premises data

The last decade has brought significant advancements and innovations across the data management landscape, spanning large-scale processing engines, cloud-based data warehouses, next-generation data la

The growing volume of data requires skills to deal with dozens of new challenges like how to ingest streaming mutable data? How to build and cache index for a fast query? How to analyze data with ML?

As Spotad is supporting millions of queries per second, in order to make data reliable and easily accessible, a well-designed data lake is one of our most important business aspects. In this presentat

Presented by Shreya Pal, Cognizant Data lakes have been around for almost a decade since the term 'data lake' was first coined. The major breakthrough was the advent of cloud around big data technolo

As more analytics workloads shift to the cloud, more customers are motivated to 'unstick' their on-premises data warehouse, data lake, and analytics platforms. Join us to learn how Google Cloud and ou

The convergence of machine learning and the data lake offers businesses new opportunities to increase the pace of innovation, make better decisions, and win new customers. AWS has an incredible array

Acquia Marketing Cloud helps marketing teams understand, personalize, and engage with users on any channel. Our product suite is open, data first, and machine learning forward. For us, this translates