ProjectPro

JUNE 6, 2025

However, this does not mean just Hadoop but Hadoop along with other big data technologies like in-memory frameworks, data marts, discovery tools ,data warehouses and others that are required to deliver the data to the right place at right time.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

JUNE 6, 2025

Decide the process of Data Extraction and transformation, either ELT or ETL (Our Next Blog) Transforming and cleaning data to improve data reliability and usage ability for other teams from Data Science or Data Analysis. Dealing With different data types like structured, semi-structured, and unstructured data.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Let's delve deeper into the essential responsibilities and skills of a Big Data Developer: Develop and Maintain Data Pipelines using ETL Processes Big Data Developers are responsible for designing and building data pipelines that extract, transform, and load (ETL) data from various sources into the Big Data ecosystem.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

MARCH 17, 2014

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Image Credit: twitter.com There are hundreds of companies like Facebook, Twitter, and LinkedIn generating yottabytes of data. What is Big Data according to EMC? What is Hadoop?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

JUNE 4, 2015

In our earlier articles, we have defined “What is Apache Hadoop” To recap, Apache Hadoop is a distributed computing open source framework for storing and processing huge unstructured datasets distributed across different clusters. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors?

Hadoop 52

Hadoop Architecture IT Java 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Electronics 52

ProjectPro

FEBRUARY 1, 2018

Apache Hadoop has become the go-to framework within the big data ecosystem for running and managing big data applications on large hardware hadoop clusters in distributed environments.Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli offered his perspective on the latest release of Hadoop 3.0

Hadoop 52

Hadoop Food Healthcare Cloud Computing 52