ChaosSearch brings key capabilities like full tech search to data bricks enabling log and event analytics for observable and security use cases natively in the data lakehouse to deploy chaos search in your data bricks workspace. Check out our 2 minute demo of ChaosSearch running on Databricks.

ChaosSearch + Databricks Deliver on the best of Databricks (open Spark-based data lakehouse) and ELK (efficient search, flexible live ingestion, API/UI) via ChaosSearch on Databricks. Log analytics for observability / security with unlimited retention at a fraction of the cost now with Databricks’ AI/ML. Watch as ChaosSearch CEO, Ed Walsh, shares the power of ChaosSearch in your Databricks environment.

What are the 7 challenges of data analytics? This preview highlights the series that Thomas Hazel, CTO & Founder of ChaosSearch will cover.

What is a data lifecycle? From birth to death, from source to destination, data seems to always be on a journey. If storage and compute were free or there were no laws like the “Right to be Forgotten” within policies such as “General Data Protection Regulation” or GDPR for short, organizations might never delete information. However, at scale data gets extremely expensive and customers do have liberties with regards to governance and sovereignty. Often it is the case that platforms have whole controls and procedures around the lifecycle of data. And in this episode, we will focus on the complexity of scale when it comes to the day in the life of data.

The first 5 challenges of #bigdataanalytics have been solved, bringing us closer to the end of the #datajourney. And here is where it starts getting real: Data Analytics. Today, there are struggles between operational and business analysis departments. SQL and ML functionality natively without data movement or duplication. How can you access and share the data timely, and efficiently, without data movement or duplication or an insane cost increase? Thomas Hazel shares his insights on how any organization can overcome this challenge, easily.

What are data platforms? A data platform (or more topical, “cloud data platform”) is an integrated set of technologies that collectively meet an organization’s end-to-end data needs. In totality, it enables the storage, delivery, and governance of company data, as well as a security layer for users and applications. The heart of a platform is an actual database where it might be better called a data “analytics” platform or in our case big data analytics platform. Learn more about data platforms and how the ChaosSearch platform solves the challenges faced in big data analytics.

Hear about David Noblet's work as Co-Founder + Chief Architect at ChaosSearch.

To coincide with our overview, watch this brief demo on how ChaosSearch can help with your big data analytics challenge of data preparation & governance.

ChaosSearch complements monitoring-focused observability solutions to meet the scale, cost and complexity challenges of operational log analytics.ChaosSearch transforms your cloud object storage into a hot data analytical datalake. Here is how ChaosSearch greatly simplifies the data pipeline.

Data preparation issues, particularly at scale, can be solved. How? This demo walks you through how ChaosSearch helps.