AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. However, organizations face challenges in the ever-expanding big data landscape where new tools quickly become outdated.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

ProjectPro

JUNE 4, 2015

The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis. Big data applications using Apache Hadoop continue to run even if any of the individual cluster or server fails owing to the robust and stable nature of Hadoop.

Hadoop 52

Hadoop Architecture IT Java 52

ProjectPro

NOVEMBER 11, 2014

This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

Hadoop 40

Hadoop Scala Machine Learning Java 40