AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. In addition to this, they make sure that the data is always readily accessible to consumers.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

RandomTrees

NOVEMBER 29, 2023

Here the practice of data warehousing and warehouse system is very important and the use of right modelling techniques has become a very important factor in todays’ competitive world. In this choice, Big Data will play an important role and its choice is also inevitably crucial in the Business Intelligence and related systems.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Data storage and processing. Data cleansing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. It should also enable easy sharing of insights across the organization.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Step 3: Data Cleansing This is one of the most critical data preparation steps.

Big Data 52

Big Data Hadoop AWS Relational Database 52