ProjectPro

JUNE 6, 2025

Knowing how to use these tools can help data modelers avoid wasting valuable time getting trained on the job and allow them to analyze their data sets more quickly. Data Integration and ETL Tools ETL is necessary for data modeling and vice versa. to perform ETL tasks efficiently. data warehouses).

NoSQL 40

NoSQL ETL Tools Certification SQL 40

ProjectPro

JUNE 6, 2025

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Data scientists and engineers typically use the ETL (Extract, Transform, and Load) tools for data ingestion and pipeline creation. For implementing ETL, managing relational and non-relational databases, and creating data warehouses, big data professionals rely on a broad range of programming and data management tools.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

AltexSoft

OCTOBER 8, 2021

IBM InfoSphere Information Server is equipped with plenty of connectors that cover most relational and non-relational databases, CRMs, OLAP software, and BI applications. They include NoSQL databases (e.g., MongoDB), SQL databases (e.g., MySQL), file stores (e.g., Pre-built connectors. Suitable for.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40