The success of data-driven initiatives for enterprise organizations depends largely on the quality of data available for analysis. This axiom can be summarized simply as garbage in, garbage out: low-quality data that is inaccurate, inconsistent, or incomplete often results in low-validity data analytics that can lead to poor business decision-making.

Data lakes have challenges. And until you solve those problems, efficient, cost-effective data analytics will remain out of reach. That’s why ChaosSearch is rethinking the way businesses manage and analyze their data. As Mike Leone, Senior Analyst for Data Platforms, Analytics and AI at ESG Global, and Thomas Hazel, ChaosSearch’s founder and CTO, explained in a recent webinar, ChaosSearch offers a data analytics optimization solution that makes data faster and cheaper to store and analyze.

Since the data lake concept emerged more than a decade ago, data lakes have been pitched as the solution to many of the woes surrounding traditional data management solutions, like databases and data warehouses. Data lakes, we have been told, are more scalable, better able to accommodate widely varying types of data, cheaper to build and so on. Much of that is true, at least theoretically.

Enterprise data growth is accelerating rapidly in 2021, challenging organizations to adopt cloud data retention strategies that maximize the value of data and fulfill compliance needs while minimizing costs. To meet this challenge, organizations are adopting or refining their cloud data retention strategies. In this blog post, we’ll take a closer look at the state of data retention and analytics in the cloud.

Logs are automatically-generated records of events that take place within a cloud-based application, network, or infrastructure service. These records are stored in log files, creating an audit trail of system events that can be analyzed for a variety of purposes, including: Enterprise organizations use log analytics software to aggregate, transform, and analyze data from log files, developing insights that drive business decisions and operational excellence.

To understand the value of logs—those many digital records of hardware and software events—picture a big puzzle. You put all the pieces together to make sense of them. Every day the modern enterprise generates billions of logs, each capturing a user log-in, application record change, network service interruption—as well as the messages these entities send to one another.

Innovation in hypervisor technology in the early 2000’s from both commercial and open source projects was the genesis for the public cloud as we know it today. Virtualization and Moore’s law, together with advances in storage technology, mobile and wireless, created a data explosion that continues to accelerate through today.