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

Smart Data Collective

JUNE 19, 2019

Are you frustrated by an increase in the quantity of the data that your organization handles? Many businesses globally are dealing with big data which brings along a mix of benefits and challenges. A report by China’s International Data Corporation showed that global data would rise to 175 Zettabyte by 2025.

Big Data 72

Big Data Big Data Big Data Analytics Big Data Analytics 72

Smart Data Collective

SEPTEMBER 23, 2020

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

Data Lakes 106

Data Lakes Data Warehouse Big Data Big Data 106

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. In a Hadoop cluster, data stored in the Hadoop Distributed File System (HDFS), which spreads the data across the nodes.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

Smart Data Collective

APRIL 24, 2019

Investing in analytics isn’t something to take lightly, but companies that do it well can set themselves up for success they didn’t even know was attainable. Who’s Using Analytics in Manufacturing? Broadly speaking, big data analytics is your company’s ticket to efficiency and productivity improvements.

Analytics 100

Analytics Analytics Big Data Analytics Big Data Analytics 100

Pickl AI

JULY 20, 2023

Web and App Analytics Projects: These projects involve analyzing website and app data to understand user behaviour, improve user experience, and optimize conversion rates. Defining clear objectives and selecting appropriate techniques to extract valuable insights from the data is essential.

Analytics 40

Analytics Analytics Big Data Big Data 40

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

Pickl AI

JUNE 29, 2023

It initiates the collection, indexing, and analysis of machine-generated data in real-time. It helps harness the power of big data and turn it into actionable intelligence. Moreover, it allows users to ingest data from different sources. Additionally, Splunk can process and index massive volumes of data.

Big Data Analytics 52

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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 75

Internet of Things Artificial Intelligence Artificial Intelligence Big Data Analytics 75

IBM Journey to AI blog

SEPTEMBER 4, 2024

Producers and consumers A ‘producer’, in Apache Kafka architecture, is anything that can create data—for example a web server, application or application component, an Internet of Things (IoT) , device and many others. Here are a few of the most striking examples.

Apache Kafka 59

Apache Kafka Internet of Things Data Pipeline Clustering 59

IBM Journey to AI blog

AUGUST 6, 2024

Big data analytics Serverless dramatically reduces the cost and complexity of writing and deploying code for big data applications. Additionally, serverless’ always-on capabilities mean data pipelines can be designed in a way to react to real-time changes in data and change application logic accordingly.

Cloud Computing 45

Cloud Computing Internet of Things Big Data Big Data 45

AWS Machine Learning Blog

NOVEMBER 12, 2024

Discoveries and improvements across seed genetics, site-specific fertilizers, and molecule development for crop protection products have coincided with innovations in generative AI , Internet of Things (IoT) and integrated research and development trial data, and high-performance computing analytical services.

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AWS AI AI Data Lakes 111

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

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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 122

Cloud Computing Big Data Big Data Internet of Things 122

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

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

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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

Pickl AI

JANUARY 16, 2024

Customer Insights Specialist Deciphering consumer behaviour through data, providing invaluable insights for marketing strategies and product development. IoT Data Analyst Analysing data generated by Internet of Things (IoT) devices, extracting meaningful patterns and trends for improved efficiency and decision-making.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Analytics 52

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

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 119

Cloud Computing Internet of Things Big Data Big Data 119