Towards Data Science

JANUARY 16, 2024

When I heard the words ‘decentralised data architecture’, I was left utterly confused at first! In my then limited experience as a Data Engineer, I had only come across centralised data architectures and they seemed to be working very well. Result: Data warehouse was born. So what was missing?

Data Warehouse 64

Data Warehouse Data Architecture Relational Database NoSQL 64

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

MAY 4, 2023

Data engineering is all about data storage and organizing and optimizing warehouses plus databases. It helps organizations understand big data and helps in collecting, storing, and analyzing vast amounts of data, using technical skills related to NoSQL, SQL, and hybrid infrastructures.

Data Engineering 52

Data Engineering Data Engineer Engineering Banking 52

ProjectPro

FEBRUARY 16, 2023

In fact, approximately 70% of professional developers who work with data (e.g., data engineer, data scientist , data analyst, etc.) According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. use SQL, compared to 61.7%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

JUNE 6, 2015

Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. The goal of BI is to create intelligence through Data. But there is also Data Quality. So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

NOVEMBER 14, 2015

This data can be analysed using big data analytics to maximise revenue and profits. We need to analyze this data and answer a few queries such as which movies were popular etc. To this group, we add a storage account and move the raw data. Then we create and run an Azure data factory (ADF) pipelines.

Hadoop 52

Hadoop Project Big Data Healthcare 52