ProjectPro

JUNE 6, 2025

Leveraging data in analytics, data science, and machine learning initiatives to provide business insights is becoming increasingly important as organizations' data production, sources, and types increase. Extract The extract step of the ETL process entails extracting data from one or more sources.

Project 40

Project Non-relational Database Business Analyst Relational Database 40

ProjectPro

JUNE 6, 2025

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 40

Big Data Hadoop Relational Database AWS 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 Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Data Migration Project to Consolidate Multiple Databases Into a Single System Companies are missing out on some of the insights that consumer data across many platforms can offer. This necessitates data consolidation. Use any of the banking datasets available on Kaggle for this project.

Project 40

Project Google Cloud AWS MongoDB 40

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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 BI 40