Remove Aggregated Data Remove MongoDB Remove Unstructured Data
article thumbnail

Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

article thumbnail

What is a Data Pipeline (and 7 Must-Have Features of Modern Data Pipelines)

Striim

Striim supported American Airlines by implementing a comprehensive data pipeline solution to modernize and accelerate operations. To achieve this, the TechOps team implemented a real-time data hub using MongoDB, Striim, Azure, and Databricks to maintain seamless, large-scale operations.

article thumbnail

Most important Data Engineering Concepts and Tools for Data Scientists

DareData

Here are a couple of resources to learn more: Data Talks Club Data Ingestion Week Coder2J Airflow Tutorial Data Storage In the context of data engineering, data storage refers to the systems and technologies that are used to store and manage data within an organization.

article thumbnail

Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

article thumbnail

14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

This is an entry-level database certification, and it is a stepping stone for other role-based data-focused certifications, like Azure Data Engineer Associate, Azure Database Administrator Associate, Azure Developer Associate, or Power BI Data Analyst Associate. Skills acquired : Core data concepts. Data storage options.

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 2- Internal Data transformation at LakeHouse.

article thumbnail

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.