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

Data Engineering Podcast

JUNE 11, 2021

Summary Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. No more scripts, just SQL.

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem Data Warehouse 100

ProjectPro

JUNE 6, 2025

Recommended Reading: Data Analyst Salary 2022-Based on Different Factors Data Engineer Data engineers are responsible for developing, constructing, and managing data pipelines. Data engineers also process collected data in batches and match its format to the stored data.

Data Science 56

Data Science Data Mining Data Architect BI 56

ProjectPro

JUNE 6, 2025

Imagine being able to communicate in different languages; that’s what these API clients provide, allowing a wide range of application development environments to interact with Hive data. Master Hive with ProjectPro’s Hands-on Big Data Projects! How does Hive work?

Big Data 40

Big Data Architecture Project Hadoop 40

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective.

Cloud 50

Cloud Hadoop Healthcare Big Data Ecosystem 50

Knowledge Hut

DECEMBER 21, 2023

What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 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. No infrastructure to maintain and scale : The customers just need to store, process, and analyze big data.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52