Smart Data Collective

APRIL 8, 2020

The data collected in the system may in the form of unstructured, semi-structured, or structured data. This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools.

Data Warehouse 144

Data Warehouse Big Data Big Data Big Data Analytics 144

Data Science Dojo

JULY 3, 2024

Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

AWS Machine Learning Blog

NOVEMBER 8, 2023

In this era of cloud computing, developers are now harnessing open source libraries and advanced processing power available to them to build out large-scale microservices that need to be operationally efficient, performant, and resilient. His knowledge ranges from application architecture to big data, analytics, and machine learning.

AWS 120

AWS Cloud Computing ML ML 120

Pickl AI

FEBRUARY 10, 2025

Covering essential topics such as EC2, S3, security, and cost optimization, this guide is designed to equip candidates with the knowledge needed to excel in AWS-related interviews and advance their careers in cloud computing. Common use cases include: Backup and restore Data archiving Big Data Analytics Static website hosting 5.

AWS 52

AWS Cloud Computing Database Big Data Analytics 52

Pickl AI

APRIL 6, 2023

Having experience using at least one end-to-end Azure data lake project. Strong skills in working with Azure cloud-based environment with delta lake implementation. Hands-on experience working with SQLDW and SQL-DB. Knowledge in using Azure Data Factory Volume. What are the skills required for an Azure Data Engineer?

Azure 52

Azure Data Engineer Data Engineering Data Engineering 52

Pickl AI

OCTOBER 11, 2024

Summary: DBMS architecture consists of several key components that work in harmony to manage data efficiently. Introduction In today’s data-driven world, the ability to efficiently manage and manipulate vast amounts of information is paramount for organisations across industries.

Database 52

Database SQL Big Data Analytics Big Data Analytics 52

IBM Journey to AI blog

JULY 6, 2023

Both data science and machine learning are used by data engineers and in almost every industry. It’s also necessary to understand data cleaning and processing techniques. Healthcare companies are using data science for breast cancer prediction and other uses.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70