Remove Cloud Storage Remove Data Ingestion Remove MongoDB Remove Structured Data
article thumbnail

Most important Data Engineering Concepts and Tools for Data Scientists

DareData

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. DigDag: An open-source orchestrator for data engineering workflows.

article thumbnail

Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

15+ Best Data Engineering Tools to Explore in 2023

Knowledge Hut

Key features: Interactive data exploration Real-time reporting Easy data modeling 3. MongoDB MongoDB is a NoSQL document-oriented database that is widely used by data engineers for building scalable and flexible data-driven applications. Some of its key features are mentioned here.

article thumbnail

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

article thumbnail

The Good and the Bad of Hadoop Big Data Framework

AltexSoft

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. It lets you run MapReduce and Spark jobs on data kept in Google Cloud Storage (instead of HDFS); or.

Hadoop 59
article thumbnail

Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.