Smart Data Collective

SEPTEMBER 23, 2020

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lakes 106

Data Lakes Data Warehouse Big Data Big Data 106

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Smart Data Collective

JUNE 19, 2019

As such, you should concentrate your efforts in positioning your organization to mine the data and use it for predictive analytics and proper planning. The Relationship between Big Data and Risk Management. Big data analytic tools provide essential metrics that you can use to monitor your production.

Big Data 71

Big Data Big Data Big Data Analytics Big Data Analytics 71

Pickl AI

JUNE 29, 2023

Furthermore, The platform’s versatility extends beyond data analysis. Moreover, one needs to have some proficiency in data analytics and query languages. Learning Splunk equips individuals with valuable data analysis skills, which are highly sought after in today’s data-driven world.

Big Data Analytics 52

Big Data Analytics Big Data Analytics Big Data Big Data 52

Pickl AI

JANUARY 16, 2024

Trends shaping careers, like AI integration and real-time analytics, highlight the evolving industry demands. The Data Analyst career growth section emphasises the value of specialisation in a field with substantial job openings in India. ’ In this digital era, Data Analysts fuel innovation.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Analytics 52

Smart Data Collective

AUGUST 14, 2019

The healthcare sector is heavily dependent on advances in big data. Healthcare organizations are using predictive analytics , machine learning, and AI to improve patient outcomes, yield more accurate diagnoses and find more cost-effective operating models. Big data analytics: solutions to the industry challenges.

Big Data Analytics 78

Big Data Analytics Big Data Analytics Big Data Big Data 78

Mlearning.ai

AUGUST 18, 2023

As a discipline that includes various technologies and techniques, data science can contribute to the development of new medications, prevention of diseases, diagnostics, and much more. Utilizing Big Data, the Internet of Things, machine learning, artificial intelligence consulting , etc.,

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52

Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Data Science Dojo

JANUARY 12, 2023

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. However, instead of using Hadoop, data lakes are increasingly being constructed using cloud object storage services. Which one is right for your business?

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Dataconomy

AUGUST 9, 2023

This data can then be collected, analyzed, and utilized to gain insights, make informed decisions, and optimize processes. This data includes information about user behavior, preferences, locations, interactions, transactions, and more. IoT and connected devices : The Internet of Things has played a crucial role in datafication.

Artificial Intelligence 172

Artificial Intelligence Artificial Intelligence AI AI 172

Pickl AI

AUGUST 24, 2023

This minimizes the risk of data loss and downtime. Innovation: Cloud Computing encourages innovation by providing access to advanced technologies and services, such as artificial intelligence, machine learning, big data analytics, and more.

Cloud Computing 52

Cloud Computing Big Data Analytics Big Data Analytics Machine Learning 52

Dataconomy

APRIL 20, 2023

Digit-computers are capable of processing and analyzing vast amounts of data quickly and accurately, which has enabled significant advances in fields like artificial intelligence, machine learning, and big data analytics.

Artificial Intelligence 154

Artificial Intelligence Artificial Intelligence Cloud Computing Internet of Things 154

Dataconomy

APRIL 20, 2023

Digit-computers are capable of processing and analyzing vast amounts of data quickly and accurately, which has enabled significant advances in fields like artificial intelligence, machine learning, and big data analytics.

Artificial Intelligence 103

Artificial Intelligence Artificial Intelligence Cloud Computing Internet of Things 103

IBM Journey to AI blog

FEBRUARY 6, 2024

Cloud-based applications and services Cloud-based applications and services support myriad business use cases—from backup and disaster recovery to big data analytics to software development. Uber, for example, depends on a microservices architecture to build and release its ride-hailing and food-delivery services quickly.

Cloud Computing 107

Cloud Computing Big Data Big Data AWS 107

IBM Journey to AI blog

JUNE 29, 2023

It integrates advanced technologies—like the Internet of Things (IoT), artificial intelligence (AI) and cloud computing —into an organization’s existing manufacturing processes. Industry 4.0

Internet of Things 60

Internet of Things Artificial Intelligence Artificial Intelligence Big Data Analytics 60

IBM Journey to AI blog

MARCH 20, 2024

artificial intelligence (AI) , edge computing, the Internet of Things (IoT) ). Analytics With the rise of data collected from mobile phones, the Internet of Things (IoT), and other smart devices, companies need to analyze data more quickly than ever before.

Cloud Computing 96

Cloud Computing Internet of Things Big Data Big Data 96