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Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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The Top 25 Data Engineering Influencers and Content Creators on LinkedIn

Databand.ai

Bob also hosts The Engineering Side of Data podcast , which is dedicated to discussions around data engineering and features a variety of guests from the data engineering space. His most passionate topics include MLOps, machine learning, data quality and data governance.

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Data Lake vs Data Warehouse - Working Together in the Cloud

ProjectPro

Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake? What is a Data lake?

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Azure Data Engineer Resume

Edureka

Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. Data ingestion, transformation, and storage are among their responsibilities, as are data governance and security.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

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How to Become an Azure Data Engineer in 2023?

ProjectPro

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

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Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

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