Systems | Development | Analytics | API | Testing

April 2021

Reasons Why Cloud Migrations Fail & Ways to Succeed

Organizations are moving big data from on-premises to the cloud, using best-of-breed technologies like Databricks, Amazon EMR, Azure HDI, and Cloudera, to name a few. However, many cloud migrations fail. Why? And, how can you overcome the barriers and succeed? Join Chris Santiago, Director of Solution Engineering, as he describes the biggest pain points and how you can avoid them, and make your move to the cloud a success.

Cox Automotive Runs Robust Pipelines on Databricks with Unravel

Cox Automotive is a large, global business. It’s part of Cox Enterprises, a media conglomerate with a strong position in the Fortune 500, and a leader in diversity. Cox also has a strong history of technological innovation, with its core cable television business serving as a leader in the growth and democratization of media over the last several decades.

AI/ML without DataOps is just a pipe dream!

Let’s start with a real-world example from one of my past machine learning (ML) projects: We were building a customer churn model. “We urgently need an additional feature related to sentiment analysis of the customer support calls.” Creating the data pipeline to extract this dataset took about 4 months! Preparing, building, and scaling the Spark MLlib code took about 1.5-2 months!

DataOps vs DevOps

The exponential adoption of IT technologies over the past several decades has had a profound impact on organizations of all sizes. Whether it is a small, medium, or large enterprise, the need to create web applications while managing an extensive set of data effectively is high on every CIO’s priority list. As a result, there has been an ongoing effort to implement better approaches to software development, data analysis, and data management.

Mastering Databricks Environments with Unravel Data

Databricks is a great solution for customers looking to unlock the powerful use cases that Spark enables, with the high performance of Databricks and the convenience of a managed service. Databricks is available in AWS, Microsoft Azure, and GCP clouds. If you are already a Databricks customer, you want to get the most out of your investment - and if you're considering Databricks, you'll be wondering how hard it is to move to the platform, and how to optimize your investment once you get there.