Going Beyond Observability for Spark Applications & Databricks Environments

Join Chris Santiago, Solutions Engineer Director at Unravel Data, as he takes you through Unravel’s approach to getting better and finer grain visibility with Spark applications and how to tune and optimize them for resource efficiency. An overview of out of the box tools like Ganglia and their overall lack of visibility on Databricks jobs How Unravel helps you gain finer grain visibility, observability, monitoring into Spark data pipelines How Unravel can recommend better configurations and tuning of Spark applications.

Major Fortune 100 Brands Choose the Unravel Data Platform

It’s hard to believe that Unravel Data was founded eight years ago — though the first few years were dedicated to defining and building our initial product. Since this time, the company has raised several rounds of funding, released several versions of our flagship DataOps Platform, and is being used by some of the world’s leading brands to improve the efficiency and reliability of their data pipelines.


Inventory management with BigQuery and Cloud Run

Many people think of Cloud Run just as a way of hosting websites. Cloud Run is great at that, but there's so much more you can do with it. Here we'll explore how you can use Cloud Run and BigQuery together to create an inventory management system. I'm using a subset of the Iowa Liquor Control Board data set to create a smaller inventory file for my fictional store. In my inventory management scenario we get a csv file dropped into Cloud Storage to bulk load new inventory.


Enterprise Data Warehouses: Definition and Guide

An enterprise data warehouse is critical to the long-term viability of your business. To be competitive, modern companies must be agile and make smart business decisions based on data, not hunches. Unfortunately, important data is often spread across multiple departments and teams, creating siloed thinking and making it challenging for leaders to get a holistic view of the business.


Using SQL to democratize streaming data

Streaming analytics is crucial to modern business – it opens up new product opportunities and creates massive operational efficiencies. In many cases, it’s the difference between creating an outstanding customer experience versus a poor one – or losing the customer altogether. However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data.