Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

Data Lakes 222

Data Lakes Data Warehouse Hadoop Machine Learning 222

AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. The data lake environment is required to configure an AWS Glue database table, which is used to publish an asset in the Amazon DataZone catalog.

Machine Learning 112

Machine Learning Machine Learning Data Governance ML 112

Data Science Dojo

JULY 6, 2023

It integrates seamlessly with other AWS services and supports various data integration and transformation workflows. Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics. Airflow An open-source platform for building and scheduling data pipelines.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

AWS Machine Learning Blog

NOVEMBER 12, 2024

Their data pipeline (as shown in the following architecture diagram) consists of ingestion, storage, ETL (extract, transform, and load), and a data governance layer. Multi-source data is initially received and stored in an Amazon Simple Storage Service (Amazon S3) data lake.

AWS 104

AWS AI AI Data Lakes 104

Pickl AI

SEPTEMBER 17, 2024

The importance of Big Data lies in its potential to provide insights that can drive business decisions, enhance customer experiences, and optimise operations. Organisations can harness Big Data Analytics to identify trends, predict outcomes, and make informed decisions that were previously unattainable with smaller datasets.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Dataconomy

SEPTEMBER 4, 2023

Text analytics is crucial for sentiment analysis, content categorization, and identifying emerging trends. Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Pickl AI

AUGUST 9, 2024

Additionally, students should grasp the significance of Big Data in various sectors, including healthcare, finance, retail, and social media. Understanding the implications of Big Data analytics on business strategies and decision-making processes is also vital.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52