How T-Mobile uses Snowflake and Databricks

Welcome to Runtime! Today: T-Mobile's data expert explains how the carrier is preparing for the future, New Relic succumbs to private equity, and the latest funding rounds in enterprise tech.

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Inside Big Magenta's data strategy

The only thing that hasn't changed about data in the nearly two decades that Vikas Ranjan has been shaping T-Mobile's data strategy is its strategic importance to the company.

Other than that, nearly everything has changed as data infrastructure evolved from big data warehouses running Hadoop on-premises gave way to cloud computing and the explosion of data management options that have flourished in its wake. And now generative AI technology is changing the equation once again, but this time in a slightly different way.

In a recent interview, Ranjan, who now manages a platform team of developers and data engineers, spoke about the differences between Snowflake and Databricks, the concept of data observability, and how to solve the skills gap in data science.

Ranjan on Snowflake and Databricks:

Telcos are much bigger in scale than many other industry verticals, and I think we are seeing a space for both. When we talk about heavy, complex, big volume data sets, the distributed processing engine is where I see Databricks playing a really critical role for us. You're talking about processing and curating hundreds of terabytes to a petabyte of data every day.

(But) not everybody is a data engineer; not everybody knows how to scan the data and make a business decision. Business users wanted to generate insights, they wanted to solve their business problem. If you want to make it simple and easy for 80% of your user community who is not a Spark user, Snowflake fits in really well.

On data observability:

The first and foremost (priority) for (data engineers) is to identify the issue with the data pipelines. The second side of looking at observability is more around data reliability or data quality. Do we have the right reconciliation rules in place? Are we seeing any drift in the data?

The third is more about cost. With the cloud you're constantly looking at ways to optimize your capacity, optimize your processing, looking at it in different ways to basically reduce waste or improve the optimization of your pipelines. And the fourth dimension is looking at it from the user's perspective. This is more about providing those insights to all the different personas from a business perspective when they're looking at the data.

On generative AI and the skills gap:

We have been kind of looking at tools like (GitHub's) Copilot. A SQL developer who is not a Java developer, or even a user (comes across) a complex transformation written in Java. The user is trying to understand what this means, and they want to use that transformation logic to basically write a simple SQL statement for XYZ business problem. The Copilots of the world are now giving you some hints … they give you enough for you to understand what the problem is that you're trying to solve with the code.

Read the full interview on Runtime.

New Relic's new boss

After years of trying and failing to turn its early momentum in infrastructure monitoring technology into an observability business, the discipline that is taking over the cloud era, this week New Relic became the latest enterprise software company acquired by private equity.

Francisco Partners and TPG bought New Relic for $6.5 billion on Monday, a 17% premium over the Friday closing price for its stock. Axios reported that New Relic hoped to command a higher price but ultimately decided to take what it could get after trying and failing to cut a similar deal earlier this year.

The usual private equity playbook seems in store following the close of the deal: New Relic struggled to break even for years, and massive cost cuts are likely in store in the near future. Francisco Partners already owns New Relic rival Sumo Logic, a February deal that prompted New Relic to warn customers that "private equity acquisitions like this can lead to uncertainty and questions" in a since-deleted blog post.

Enterprise funding

Nile raised $175 million to take on co-founder and chairman John Chambers' old friend Cisco with its networking technology.

Neon landed a $46 million Series B round for its serverless PostgreSQL database technology.

Cyble scored $24 million to build out its threat intelligence platform and vulnerability scanning business.

Socket raised a $20 million Series A round to build out its security technology, which is designed to find vulnerabilities in open-source projects.

Protect AI landed $35 million in Series A funding to help companies defend their AI projects from security attacks.

The Runtime roundup

AMD's data-center revenue declined 11% during the second quarter, a notable blip during its recent run of success after "enterprise demand was soft and cloud inventory levels were elevated at some customers" during the quarter.

AWS announced plans to launch a new cloud region in Tel Aviv, Israel, committing around $7.2 billion over the next several years to expand its presence in the Middle East.

A small cloud provider apparently called Cloudzy (I mean, come on) has been the launching pad for several recent cyberattacks carried out by hackers, according to a report.

Meanwhile, Bleeping Computer reported that other hackers are figuring out how to harness generative AI tools to launch new phishing and malware attacks, as predicted by security experts in our report earlier this year.

Microsoft changed the terms of its Microsoft 365 licenses to allow customers to run those apps on AWS, according to Directions on Microsoft, which described the changes as allowing "a very premium way to run 'Office' on WorkSpaces."

Thanks for reading — see you Thursday!