2022 Blog Data Architecture Datasets 
U-Next
AUGUST 17, 2022
Introduction to 2022 Data Engineer Roles and Responsibilities. Companies and enterprises, large and small, are built on data. Data Engineer roles and responsibilities include aiding in the collection of issues and the delivery of remedies addressing customer demand and product accessibility.
U-Next
AUGUST 10, 2022
Develop your data architecture: They design, develop, and manage data structures systematically, even while maintaining them in line with business needs. Automate Workflows: Data Engineers go into the data to identify processes that may be automated to remove manual involvement.
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Cloudera
DECEMBER 21, 2021
As data teams grow, RAZ integration with CDE will play an even more critical role in helping share and control curated datasets. We are excited to offer in Tech Preview this born-in-the-cloud table format that will help future proof data architectures at many of our public cloud customers. Modernizing pipelines.
Databand.ai
DECEMBER 20, 2022
The Top Data Analytics and Science Influencers and Content Creators on LinkedIn Ryan Yackel 2022-12-20 11:06:32 If you’re looking to brush up on all things data analytics and science, then LinkedIn certainly has no shortage of content. On LinkedIn, he posts regularly about data analytics and data science.
Rockset
AUGUST 2, 2023
With 90% of trade being transported via sea , this data is crucial to keeping the global supply chain on track but can be difficult to disentangle and take action on. In 2022, Windward embarked on several changes to its application prompting a reconsideration of its underlying data stack.
DataKitchen
JULY 3, 2023
Teams Did Not Build Current Architecture For Rapid And Low-Risk Changes Those Systems Teams have complicated in-place data architectures and tools and fear changes to what is already running. Constant Data And Tool Errors In Production Teams cannot see across all tools, pipelines, jobs, processes, datasets, and people.
Data Science Blog: Data Engineering
NOVEMBER 15, 2023
The trend towards powerful in-house cloud platforms for data and analysis ensures that large volumes of data can increasingly be stored and used flexibly. New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications.
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