Data Operations

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Let’s Talk DataOps: Jon Loyens, Co-founder and CPO of data.world

Welcome to our new interview series, “Let’s Talk DataOps!” DataOps (Data Operations) is an emerging function that controls the flow of data from source to value. This includes integrating with data sources, performing transformations on the data, converting formats, and writing or delivering data to its required destination so it can be analyzed, inputted into a model, or surfaced for end users. DataOps also encompasses the monitoring and governance of data flows, while ensuring security and scale.

In this new series we’ll be interviewing the leading thinkers in Data Operations, to discuss the state of DataOps from their point of view. Learn about what they do, their biggest challenges, and how they are utilizing DataOps to drive their businesses. For our inaugural interview, we spoke with Jon Loyens, the Co-Founder and Chief Product Officer of data.world. As a long-time technology executive in Austin, Jon has lived the rise in the trend of data and analytics as a democratizing force. In a past life, he was the VP of Engineering for Traveler Products at HomeAway, and before that, a VP of Engineering and Director of the Labs group at Bazaarvoice.

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DataOps Report Breakdown: DataOps Outlook

The chart above examines which functional areas within an organization plan to hire in DataOps. Unsurprisingly, 79% of those respondents in IT said they will hire in DataOps. The majority of Data Science, Engineering, and Analytics respondents also have plans to hire, which should come as no surprise.

What is surprising however, is that 53% of those who work in other functions also have plans to hire in DataOps. This “Other” category includes Product Management, Marketing, and even areas like Finance. This suggests business owners in almost all functional areas have the need to integrate, process, and derive value from data.

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The Definitive Data Operations Report 2017

At Nexla, we are constantly thinking about the challenges of data operations for cross-company data. We’ve spoken with hundreds of companies about the unique effort required to send and receive data across company lines. But few benchmarks exist in the market for companies looking to learn from best practices. We decided to investigate.

This first-of-its-kind survey asked over 300 respondents about how they derive value from data. We surveyed data professionals from 40 different industries, with tenures ranging from two years to more than ten. In this post, we summarize some of the key benchmarks that emerged from the study. You can read the full report here, and a brief summary in this post.

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Data Engineers: The New Kings and Queens of Artificial Intelligence

Data operations is the pick axe in the AI gold rush. Without the right data and the equipment to mine it, the promise of AI for many companies will be left unrealized. This is especially true for companies in finance, retail, healthcare, and more where you create value with the algorithms and analysis you do on data and not how you access and manage it. These companies would be wise to work with trusted software partners to build up their data operations teams. The data challenges that come with AI can’t be solved by more job listings. We’re going to need real technology to help our data engineering kings and queens process the next 180 zettabytes.

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Introducing Nexie: The Portable, Hand-Held Data Center

Today Nexla is announcing a solution for companies to run Machine learning models in their own data centers. Nexie is an ingenious piece of hardware designed by Nexla which brings machine learning into your own data center. The device can be powered on in any data center across the globe. Nexie can connect with existing storage solutions via multiplexed universal ports. Nexie comes with two ports, In & Out. The In port allows you to receive data, Out port outputs the results of the model. Multiple Nexies can be joined together to create portable clusters!

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