ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., Need for Apache Sqoop How Apache Sqoop works? Need for Flume How Apache Flume works?

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Knowledge Hut

DECEMBER 26, 2023

The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

ProjectPro

JUNE 23, 2016

Apache Sqoop is a lifesaver for people facing challenges with moving data out of a data warehouse into the Hadoop environment. Sqoop is a SQL to Hadoop tool for efficiently importing data from a RDBMS like MySQL, Oracle, etc. It can also be used to export the data in HDFS and back to the RDBMS.

Hadoop 40

Hadoop MySQL Relational Database Java 40

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

OCTOBER 8, 2021

It is possible to move datasets with incremental loading (when only new or updated pieces of information are loaded) and bulk loading (lots of data is loaded into a target source within a short period of time). MySQL), file stores (e.g., Hadoop), cloud data warehouses (e.g., Data loading. Pre-built connectors.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

DECEMBER 7, 2021

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 27, 2021

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.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40