Big Data Tools MongoDB Relational Database 
Knowledge Hut
APRIL 25, 2024
This article will discuss big data analytics technologies, technologies used in big data, and new big data technologies. Check out the Big Data courses online to develop a strong skill set while working with the most powerful Big Data tools and technologies.
Knowledge Hut
DECEMBER 21, 2023
With the help of these tools, analysts can discover new insights into the data. Hadoop helps in data mining, predictive analytics, and ML applications. Why are Hadoop Big Data Tools Needed? NoSQL databases can handle node failures. Different databases have different patterns of data storage.
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Knowledge Hut
JUNE 23, 2023
You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning. You can also post your work on your LinkedIn profile.
ProjectPro
JANUARY 19, 2022
Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. Learning Resources: How to Become a GCP Data Engineer How to Become a Azure Data Engineer How to Become a Aws Data Engineer 6.
Knowledge Hut
NOVEMBER 17, 2023
Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases.
Edureka
FEBRUARY 9, 2023
Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.
AltexSoft
JUNE 26, 2023
Semi-structured data is not as strictly formatted as tabular one, yet it preserves identifiable elements — like tags and other markers — that simplify the search. They can be accumulated in NoSQL databases like MongoDB or Cassandra. Unstructured data represents up to 80-90 percent of the entire datasphere.
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