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Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala.

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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. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

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

AltexSoft

In the EU, the General Data Protection Regulation (GDPR) sets guidelines for collecting, storing, and processing personal information. This privacy law must be kept in mind when building data architecture. It defines metrics and best practices to ensure data quality as well as data privacy and security.

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The Top 25 Data Engineering Influencers and Content Creators on LinkedIn

Databand.ai

Deepanshu’s skills include SQL, data engineering, Apache Spark, ETL, pipelining, Python, and NoSQL, and he has worked on all three major cloud platforms (Google Cloud Platform, Azure, and AWS). He is constantly seeking out knowledge and being excited by the challenge of learning something new in the data science space.