Smart Data Collective

APRIL 8, 2020

In the modern era, big data and data science are significantly disrupting the way enterprises conduct business as well as their decision-making processes. With such large amounts of data available across industries, the need for efficient big data analytics becomes paramount.

Data Warehouse 144

Data Warehouse Big Data Big Data Big Data Analytics 144

Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

AWS 138

AWS Cloud Computing Data Lakes Database 138

Smart Data Collective

OCTOBER 13, 2021

This is of great importance to remove the barrier between the stored data and the use of the data by every employee in a company. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Multi-channel publishing of data services. Prescriptive analytics.

Data Visualization 145

Data Visualization Big Data Big Data Predictive Analytics 145

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

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

Heartbeat

OCTOBER 25, 2023

e) Big Data Analytics: The exponential growth of biological data presents challenges in storing, processing, and analyzing large-scale datasets. Traditional computational infrastructure may not be sufficient to handle the vast amounts of data generated by high-throughput technologies.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

Dataconomy

MARCH 19, 2025

Hadoop as a Service (HaaS) offers a compelling solution for organizations looking to leverage big data analytics without the complexities of managing on-premises infrastructure. With the rise of unstructured data, systems that can seamlessly handle such volumes become essential to remain competitive.

Hadoop 91

Hadoop Big Data Big Data Big Data Analytics 91