Knowledge Hut

JULY 26, 2023

Database Software- Document Store (e.g.-MongoDB): MongoDB): MongoDB is a prominent database software that comes under the category of "document store" databases. Document store databases, such as MongoDB, are intended to store and manage data that is unstructured or semi-structured, such as documents.

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

MAY 31, 2023

It is also one of the most important database projects for students. Top Database Project Ideas Using MongoDB MongoDB is a popular NoSQL database management system that is widely used for web-based applications. Plus, MongoDB also enables efficient indexing, which facilitates quick query execution at scale.

Database 52

Database Coding MongoDB Project 52

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.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. The “NoSQL” part here stands for “Non-SQL” and “Not Only SQL”.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 19, 2022

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

NOVEMBER 23, 2021

With data virtualization, Pfizer managed to cut the project development time by 50 percent. In addition to the quick data retrieval and transfer, the company standardized product data to ensure consistency in product information across all research and medical units.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

NOVEMBER 14, 2015

Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. This system can even handle emergency situations if required.

Hadoop 52

Hadoop Project Big Data Healthcare 52