Every action a healthcare provider, payer, administrator, or patient takes creates new data. The challenge in healthcare is no longer finding data - but making it usable and actionable. This requires knowing what to do with the data you have, and understanding the relationships that exist within it.

Where do performance testing and monitoring fit into the Agile and DevOps development process? Implementing a process for improving the performance of your applications requires the right tools to help you do it. These tools go beyond the responsibilities of your development team to ensure that applications are tested in pre-deployment and monitored after your application is live in production. This eBook will provide the tactical advice you need to implement a strategy that works for your organization.

This white paper shows you how to spot bad data and debunks the 6 most common data quality myths. As the total volume of data around the world continues to increase, so will the volume of bad data. Poor data quality costs companies an average of $15 million per year (and rising), according to Gartner.

This handbook takes a deep dive into the IT architectures developed by 3 different enterprises for big data, real-time analytics, and ETL projects on Amazon Web Services (AWS) using Talend.

Bugfender grants you fast remote access to your applications' log files on users' devices - wherever they are in the world. Bugfender logs virtually everything, going beyond simple app crashes. It even logs when the device is offline.

Read this ebook to know about common tactical and strategic mistakes to avoid when implementing Hadoop, which are identified by executives and IT teams.

Whether you are a product manager looking to get to market fast with powerful and intuitive visual analytics for your customers or a business owner looking to differentiate your solution to gain a competitive advantage we hope you will find this paper useful.

Join Qlik's Global Market Intelligence lead and former Gartner analyst Dan Sommer to learn why 2018 is the year for the "de-silofication" of data.