CDW Research Hub

MAY 28, 2021

As we move forward, hybrid cloud continues to be the data storage strategy that helps organizations gain cost-effectiveness and increase data mobility between on-premises, public cloud and private cloud without compromising data integrity. Investment in AI.

Optimization 52

Optimization Deep Learning Enterprise Software 52

BizAcuity

APRIL 6, 2022

To predict movements and volatility, machine learning and deep learning algorithms are widely used by organizations to strategize and prepare accordingly. Not using AI for predicting crypto price movements can be an extremely risky measure in the current financial climate.

Data Analytics 52

Data Analytics Analytics B2B Deep Learning 52

O'Reilly on Data

DECEMBER 12, 2019

More structured approaches to sensitivity analysis include: Adversarial example searches : this entails systematically searching for rows of data that evoke strange or striking responses from an ML model. Figure 1 illustrates an example adversarial search for an example credit default ML model.

Machine Learning 197

Machine Learning Modeling Testing Risk Management 197

Ontotext

NOVEMBER 6, 2019

GraphDB Workbench is the interface for Ontotext’s semantic graph database, which provides the core infrastructure including modelling agility, data integration, relationship exploration and cross-enterprise semantic data publishing and consumption. The Plugins.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

AWS Big Data

JUNE 26, 2023

Create the FindMatches ML transform On the AWS Glue console, expand Data Integration and ETL in the navigation pane. Under Data classification tools, choose Record Matching. He believes deep learning will power future technology growth. This will open the ML transforms page. Choose Create transform.

Insurance 78

Insurance Visualization Data Lake Metrics 78

Smarten

APRIL 19, 2024

Data Integration – Businesses can incorporate storage and data security services and infrastructure, thereby making it easier to avoid data silos and to achieve data integration and single-point-of-contact data analytics.

Analytics 52

Analytics Predictive Modeling KPI Machine Learning 52

O'Reilly on Data

MARCH 20, 2019

Watermarking is a term borrowed from the deep learning security literature that often refers to putting special pixels into an image to trigger a desired outcome from your model. It seems entirely possible to do the same with customer or transactional data. Watermark attacks. Disparate impact analysis: see section 1.

Modeling 226

Modeling Machine Learning Predictive Modeling Consulting 226

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 77

Machine Learning Manufacturing Cost-Benefit Deep Learning 77

IBM Big Data Hub

NOVEMBER 14, 2023

Serve : Build cloud services for data products through automation and platform service technology so they can be operated securely at global scale. Realize: Instrument the data product services to enable adherence to risk and compliance controls with event and metrics data integrated to financial management.

Strategy 110

Strategy Cost-Benefit Data-driven Measurement 110

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Cloudera

NOVEMBER 19, 2020

Cloudera Data Platform (CDP) is a solution that integrates open-source tools with security and cloud compatibility. Governance: With a unified data platform, government agencies can apply strict and consistent enterprise-level data security, governance, and control across all environments.

Machine Learning 114

Machine Learning Data-driven Modeling Deep Learning 114

CIO Business Intelligence

MARCH 22, 2022

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. We keep feeding the monster data. We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Ontotext

FEBRUARY 26, 2024

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Sisense

AUGUST 6, 2020

Today, we’re developing AI in an era where data is treated as code, or at least as an extension of code, because the code alone cannot achieve deep learning without the data. Moreover, training data must conform to the app design to such an extent that data preparation resembles coding.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Cloudera

FEBRUARY 4, 2019

Dinesh’s areas of expertise include IoT, Application/Data integration, BPM, Analytics, B2B, API management, Microservices, and Mobility. He currently works at Cloudera, managing their Data-in-Motion product line. He is fascinated by new technology trends including blockchain and deep learning.

IoT 73

IoT Prescriptive Analytics Digital Transformation Internet of Things 73

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Machine learning is not only appearing in more products and systems, but as we noted in a previous post , ML will also change how applications themselves get built in the future.

Machine Learning 243

Machine Learning Technology Deep Learning Data Science 243

Smart Data Collective

OCTOBER 13, 2021

As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields).

Visualization 132

Visualization Cost-Benefit Big Data Prescriptive Analytics 132