Data Engineer Data Lake Data Pipeline High Quality Data 
Data Engineering Weekly
MARCH 3, 2024
Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup. There will be food, networking, and real-world talks around data engineering. link] Martin Chesbrough: How to Build a Modern Data Team?
Edureka
FEBRUARY 7, 2023
An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.
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ProjectPro
FEBRUARY 21, 2023
With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? The answer is- by earning professional data engineering certifications! AWS or Azure?
Monte Carlo
AUGUST 31, 2023
As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.
Databand.ai
JULY 5, 2023
What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. Data observability tools allow teams to detect issues such as missing values, duplicate records, or inconsistent formats early on before they affect downstream processes.
Data Engineering Podcast
JANUARY 28, 2024
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.
DataKitchen
NOVEMBER 4, 2021
Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.
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