IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Integrating conversational AI into the Internet of Things (IoT) also offers vast possibilities, enabling more intelligent and interactive environments through seamless communication between connected devices.

Enterprise 110

Enterprise Interactive Data-driven Key Performance Indicator 110

Smart Data Collective

MAY 17, 2021

Big data is at the heart of the digital revolution. Basing fleet management operations on data is not new, and in some ways, it’s always been a part of the industry. Basing fleet management operations on data is not new, and in some ways, it’s always been a part of the industry. Organizations have already realized this.

Big Data 101

Big Data Cost-Benefit IoT Machine Learning 101

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 307

Testing Machine Learning Consulting Data Quality 307

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. forward (with some folks now starting to envision what Industry 5.0

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Cloudera

SEPTEMBER 11, 2020

Much of the changes we’re seeing from retail and consumer goods leaders in terms of impact are centered around the use of data and analytics. What they have learned is that often their legacy Machine Learning models (e.g. demand forecasting) based solely on historical transaction data – really missed the mark.

Manufacturing 90

Manufacturing Forecasting Digital Transformation Sales 90

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

AWS Big Data

MAY 16, 2024

H3-based analytics empower the processing and understanding of delivery data patterns, such as peak times, popular destinations, and high-demand areas. H3 can also help create location-based profiling features for predictive machine learning (ML) models such as risk-mitigation models.

Data Warehouse 82

Data Warehouse Visualization Cost-Benefit Optimization 82

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Alation

APRIL 14, 2022

A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. It’s More Important to Know What Your Data Means Than Where It Is.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

IBM Big Data Hub

MAY 17, 2023

The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses. The flexibility of DaaS in offering a multiplicity of data collection services for different industry use cases makes it unique.

Data Collection 86

Data Collection Visualization Data-driven Unstructured Data 86

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is now able to automatically create and maintain materialized views and then transparently rewrite queries to use the materialized views using the machine-learned automated materialized view autonomics feature in Amazon Redshift. Aamer Shah is a Senior Engineer in the Amazon Redshift Service team.

Data Warehouse 98

Data Warehouse Cost-Benefit Dashboards Optimization 98

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

CIO Business Intelligence

JANUARY 20, 2023

Here’s what to consider: Ingesting the data : To be able to analyze more data at greater speeds, organizations need faster processing via high-powered servers and the right chips for AI—whether CPUs or GPUs. Protecting the data : Cyber threats are everywhere—at the edge, on-premises and across cloud providers.

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137

O'Reilly on Data

MARCH 24, 2020

If you’re basing business decisions on dashboards or the results of online experiments, you need to have the right data. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0 Data professionals spend an inordinate amount on time cleaning, repairing, and preparing data.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346