CIO Business Intelligence

MARCH 13, 2024

L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%). Le reti neurali sono il modello di machine learning più utilizzato oggi. Che cosa posso fare con l’IA?

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

Insurance 81

Insurance Visualization Data Lake Metrics 81

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). The platform has three powerful components: the watsonx.ai

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. Transform CSV to Parquet Raw CSV files are converted to Parquet data format with AWS Glue.

Data Lake 86

Data Lake Deep Learning Modeling Interactive 86

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

MARCH 22, 2022

How do you introduce AI into your data and analytics infrastructure? To companies entrenched in decades-old business and IT processes, data fiefdoms, and legacy systems, the task may seem insurmountable. Which type(s) of storage consolidation you use depends on the data you generate and collect. . Outcomes you can expect.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

MAY 16, 2024

H3 indexing and related H3 spatial functions are now available for Amazon Redshift spatial analytics. For more information or to get started with Amazon Redshift spatial analytics, see the documentation for querying spatial data , spatial functions , and the spatial tutorial.

Data Warehouse 103

Data Warehouse Visualization Cost-Benefit Optimization 103

Domino Data Lab

APRIL 3, 2019

Data coming from machines tends to land (aka, data at rest ) in durable stores such as Amazon S3, then gets consumed by Hadoop, Spark, etc. Somehow, the gravity of the data has a geological effect that forms data lakes. DG emerges for the big data side of the world, e.g., the Alation launch in 2012.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. models are trained on IBM’s curated, enterprise-focused data lake. That’s where the foundation model enters the picture. All watsonx.ai

Modeling 59

Modeling Cost-Benefit Data Lake Machine Learning 59

Cloudera

FEBRUARY 4, 2019

Process millions of real-time messages per second to feed into your data lake or for immediate streaming analytics. Streaming Analytics – Analyze millions of streams of data in real-time using advanced techniques such as aggregations, time-based windowing, content-filtering etc.,

IoT 72

IoT Prescriptive Analytics Digital Transformation Internet of Things 72

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. 8 Critical Analytics Tools for Cloud Environments. Predictive Transformation.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

NOVEMBER 15, 2023

The analytics team is waiting to engage with our customers and partners at the analytics kiosk in the expo hall. For the latest and greatest with Amazon Redshift , our cloud data warehousing solution, I’ve curated a few must-attend sessions. Take a look, plan your week, and soak in the learning!

Data Lake 67

Data Lake Data Warehouse B2B Deep Learning 67

DataRobot Blog

MARCH 7, 2023

The DataRobot AI Platform seamlessly integrates with Azure cloud services, including Azure Machine Learning, Azure Data Lake Storage Gen 2 (ADLS), Azure Synapse Analytics, and Azure SQL database. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59