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Tips to Build a Robust Data Lake Infrastructure

DareData

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data. If you need help to understand how these tools work, feel free to drop us a message!

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

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Analytics Engineer: Job Description, Skills, and Responsibilities

AltexSoft

The development of new tools and the improvement of old ones has led to the transformation of the traditional data roles, simplifying some job aspects and complicating other ones. Companies start hiring that one data guy or gal that wears all the hats — knows the complete data stack from both the engineering and analytics sides.

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100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. What is the best way to capture streaming data in Azure?