O'Reilly Media - Data
APRIL 11, 2018
It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.
TechCrunch
NOVEMBER 19, 2020
Data engineering is one of these new disciplines that has gone from buzzword to mission critical in just a few years. As data has exploded, so has their challenge of doing this key work, which is why a new set of tools has arrived to make data engineering easier, faster and better than ever.
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CIO
SEPTEMBER 14, 2023
What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.
CIO
JANUARY 17, 2023
It shows in his reluctance to run his own servers but it’s perhaps most obvious in his attitude to data engineering, where he’s nearing the end of a five-year journey to automate or outsource much of the mundane maintenance work and focus internal resources on data analysis. It’s not a good use of our time either.”
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In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.
TechCrunch
JANUARY 20, 2022
Prophecy , a low-code platform for data engineering, today announced that it has raised a $25 million Series A round led by Insight Partners. These enterprises, Bains noted, often sit on tens of thousands of data pipelines that run on-premises. . So I’m like: we can fix this,” Prophecy co-founder Raj Bains said.
CIO
AUGUST 9, 2022
What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.
Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale
Workshop video modules include: Breaking down data silos. Integrating data from third-party sources. Developing a data-sharing culture. Combining data integration styles. Translating DevOps principles into your data engineering process. Using data models to create a single source of truth.
Speaker: Mindy Chen, Director of Decision Science, Hudl
Mindy Chen, Director of Decision Science at Hudl, will take us on a journey through the challenges and opportunities she has seen when building a data team from scratch. Growing from 3 data engineers to a robust team of 20, Hudl has been on a journey to establish their data capability.
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