Data Lake MongoDB NoSQL Unstructured Data 
U-Next
MARCH 1, 2023
A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial.
Rockset
APRIL 27, 2021
Many developers use NoSQL databases in order to ingest unstructured and schemaless data. When it comes to understanding the data by writing queries that join, aggregate, and search, it becomes more challenging. In this twitch stream, we created a MongoDB Atlas instance.
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Databand.ai
DECEMBER 13, 2022
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 specialties include Microsoft SQL Server, Azure Databricks, Azure Data Factory, SQL Server Integration Services (SSIS), and Azure Data Lake.
DareData
JANUARY 30, 2023
For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of NoSQL databases include MongoDB or Cassandra. Introduction to Designing Data Lakes in AWS.
ProjectPro
NOVEMBER 14, 2015
Such unstructured data has been easily handled by Apache Hadoop and with such mining of reviews now the airline industry targets the right area and improves on the feedback given. Tools/Tech stack used: The tools and technologies used for such weblog trend analysis using Apache Hadoop are NoSql, MapReduce, and Hive.
AltexSoft
JUNE 26, 2023
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.
Knowledge Hut
NOVEMBER 7, 2023
You can swiftly provision infrastructure services like computation, storage, and databases, as well as machine learning, the internet of things, data lakes and analytics, and much more. " Instead of relying on nearby hard drives and personal data centers, it requires storing and accessing data on distant servers.
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