Precisely

JANUARY 9, 2025

The ETL (extract, transform, and load) technology market also boomed as the means of accessing and moving that data, with the necessary translations and mappings required to get the data out of source schemas and into the new DW target schema. Then came Big Data and Hadoop! The big data boom was born, and Hadoop was its poster child.

Data Warehouse 119

Data Warehouse Hadoop Data Governance Data Lakes 119

Pickl AI

JANUARY 27, 2025

Hadoop emerges as a fundamental framework that processes these enormous data volumes efficiently. This blog aims to clarify Big Data concepts, illuminate Hadoops role in modern data handling, and further highlight how HDFS strengthens scalability, ensuring efficient analytics and driving informed business decisions.

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. At the heart of this process lie ETL Tools—Extract, Transform, Load—a trio that extracts data, tweaks it, and loads it into a destination. Choosing the right ETL tool is crucial for smooth data management. What is ETL?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

How to Learn Machine Learning

APRIL 26, 2025

The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark). Tools like Python (with pandas and NumPy), R, and ETL platforms like Apache NiFi or Talend are used for data preparation before analysis.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Becoming Human

JANUARY 23, 2023

- a beginner question Let’s start with the basic thing if I talk about the formal definition of Data Science so it’s like “Data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis” , is the definition enough explanation of data science?

Data Science 105

Data Science Big Data Big Data Deep Learning 105

ODSC - Open Data Science

SEPTEMBER 27, 2023

Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

IBM Journey to AI blog

JANUARY 18, 2023

While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale. As it is clear from the definition above, unlike data fabric, data mesh is about analytical data.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52