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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

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How to Design a Modern, Robust Data Ingestion Architecture

Monte Carlo

Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data. Used for identifying and cataloging data sources. Data Storage with Apache HBase : Provides scalable, high-performance storage for structured and semi-structured data.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Data sources can be broadly classified into three categories.

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Business Intelligence vs Artificial Intelligence-Battle of the Brains

ProjectPro

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

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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.

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15 Top Machine Learning Projects for Final Year Students

ProjectPro

Recommendation engines are popular in media, entertainment, and shopping. To build such ML projects, you must know different approaches to cleaning raw data. This type of application is beneficial in searching, mobile application development, and social media apps. also have the same feature.

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Is the data warehouse going under the data lake?

ProjectPro

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream dataData Lakes fulfil a critical need.