If your company is increasingly relying on Big Data, you’ve probably encountered issues with managing all the information in your various workloads.
Keeping track of everything happening in every cluster, for example, can be a challenge, especially when several teams are working at once.
Thankfully, there are a number of tools available to help you manage and effectively use all the information in your Big Data pool.
In this edition of Tech We Like, we’re looking at two of those tools: Azure Databricks and Unravel.Azure Databricks
An automated cluster management tool for AI, data engineering, and data science, Azure Databricks utilizes what’s known as “notebooks” that make it easy for constant and iterative Big Data processing.
For example, a data scientist or data engineer at your company can quickly fire up a cluster via Azure Databricks, work on it, and once that work is done, simply destroy the cluster — all through a single interface. This not only increases efficiency, it helps keep your data from becoming cluttered and disorganized.
In addition, Azure Databricks plays extremely well with GitHub and Bitbucket, allowing for easy collaboration. And since it integrates directly into the Azure Active Directory, security requires no real configuration.
You can learn more about Azure Databricks at their website.
In the Big Data ecosystem, there’s nothing quite like Unravel.
The tool really shines in helping companies migrate to the cloud, whether it’s partially or in full. Not only does it shine a light on clusters and the workloads happening within them, it goes a step further and actually identifies the best workloads to migrate.
Most impressive of all, Unravel is able to provide all of this with one pane of glass visibility, so you always know which workloads should be where and what’s being run on them.
You can learn more about Unravel at their website.
For more on Big Data, download our free whitepaper Big Data Made Simple.
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