Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms.

Cost-Benefit 114

Cost-Benefit Data Lake Software Machine Learning 114

KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

Data Science 158

Data Science Machine Learning Analytics Data Lake 158

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. As a machine learning problem, it is a classification task with tabular data, a perfect fit for RAPIDS. Data Ingestion. Introduction.

Machine Learning 138

Machine Learning Data Science Data Lake Modeling 138

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 83

Insurance Visualization Data Lake Metrics 83

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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. In this example, we searched for columns in our data lake that have similar Column Names ( payload type ) to district ( payload ).

Data Lake 88

Data Lake Deep Learning Modeling Interactive 88

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

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 56

Modeling Cost-Benefit Data Lake Machine Learning 56

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. However, the concept is quite abstract. Compute.

IT 342

IT Testing Experimentation Software 342

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 109

Data Warehouse Visualization Cost-Benefit Optimization 109

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. Watsonx.ai

Data Warehouse 108

Data Warehouse Machine Learning Cost-Benefit Metadata 108

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Start small with AI. Just starting out with analytics?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Alation

APRIL 14, 2022

Pushing data to a data lake and assuming it is ready for use is shortsighted. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

Metadata 59

Metadata Data Governance Modeling Data-driven 59

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. AI Platform Single-Tenant SaaS are fully managed by DataRobot and replace disparate machine learning tools, simplifying management.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59