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10 Data Engineering Topics and Trends You Need to Know in 2024

ODSC - Open Data Science

Now that we’re in 2024, it’s important to remember that data engineering is a critical discipline for any organization that wants to make the most of its data. These data professionals are responsible for building and maintaining the infrastructure that allows organizations to collect, store, process, and analyze data.

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DataOps

Dataconomy

Team structure in DataOps Effective DataOps teams consist of various roles that contribute to a seamless data lifecycle. Leadership often includes a Chief Data Scientist or Chief Analytics Officer who guides the strategy and vision. Collaboratively, team members such as: Data engineers: Who design and maintain data pipelines.

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professionals

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Best Data Engineering Tools Every Engineer Should Know

Pickl AI

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

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Top 9 AI conferences and events in USA – 2023

Data Science Dojo

The speaker is Andrew Madson, a data analytics leader and educator. The event is for anyone interested in learning about generative AI and data storytelling, including business leaders, data scientists, and enthusiasts. The event will be conducted online, making it accessible to a global audience.

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Data Observability Tools and Its Key Applications

Pickl AI

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

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What Is Data Observability and Why You Need It?

Precisely

It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation. But with all that data, there are new challenges that may prompt you to rethink your data observability strategy. Learn more here.

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6 benefits of data lineage for financial services

IBM Journey to AI blog

That’s why data pipeline observability is so important. Data lineage expands the scope of your data observability to include data processing infrastructure or data pipelines, in addition to the data itself. The Basel Committee released BCBS 239 as far back as 2013.