Analytics Vidhya

MARCH 16, 2023

Apache Oozie is a workflow scheduler system for managing Hadoop jobs. It enables users to plan and carry out complex data processing workflows while handling several tasks and operations throughout the Hadoop ecosystem.

ETL 197

ETL Hadoop Analytics Analytics 197

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. This is particularly advantageous when dealing with exponentially growing data volumes.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. Types of ETL Tools.

ETL 93

ETL Hadoop Data Warehouse Data Pipeline 93

Becoming Human

JANUARY 23, 2023

Let’s understand with an example if we consider web development so there are UI , UX , Database , Networking , and Servers and for implementing all these things we have different-different tools - technologies and frameworks , and when we have done with these things we just called this process as web development.

Data Science 105

Data Science Big Data Big Data Deep Learning 105

Smart Data Collective

MAY 20, 2019

With databases, for example, choices may include NoSQL, HBase and MongoDB but its likely priorities may shift over time. For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. The popular tools, on the other hand, include Power BI, ETL, IBM Db2, and Teradata.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

Pickl AI

NOVEMBER 15, 2023

A Data Lake is a centralized repository that allows businesses to store vast volumes of structured and unstructured data at any scale. Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible. Here it becomes important to highlight the database systems.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

JANUARY 18, 2023

Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This adds an additional ETL step, making the data even more stale. Data platform architecture has an interesting history. It was Datawarehouse.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52