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Apache Kafka Vs Apache Spark: Know the Differences

Knowledge Hut

A new breed of ‘Fast Dataarchitectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars.

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Fivetran Supports the Automation of the Modern Data Lake on Amazon S3

phData: Data Engineering

Today we want to introduce Fivetran’s support for Amazon S3 with Apache Iceberg, investigate some of the implications of this feature, and learn how it fits into the modern data architecture as a whole. Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format.

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Power BI Developer Roles and Responsibilities [2023 Updated]

Knowledge Hut

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

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Data Governance: Framework, Tools, Principles, Benefits

Knowledge Hut

The mix of people, procedures, technologies, and systems ensures that the data within a company is reliable, safe, and simple for employees to access. It is a tool used by businesses to protect their data, manage who has access to it, who oversees it, and how to make it available to staff members for everyday usage.

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The Symbiotic Relationship Between AI and Data Engineering

Ascend.io

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

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The Future of Data Analytics: Trends of Tomorrow

Knowledge Hut

Historically, data analytics was a highly technical field requiring specialized skills and expertise. However, with the emergence of no-code or low-code analytics tools, business users are now able to access and analyze data more easily.

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Data Pipeline Observability: A Model For Data Engineers

Databand.ai

Data pipelines often involve a series of stages where data is collected, transformed, and stored. This might include processes like data extraction from different sources, data cleansing, data transformation (like aggregation), and loading the data into a database or a data warehouse.