Domino Data Lab

JUNE 10, 2020

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. You can identify data drift, missing information, and other issues, and take corrective action before bigger problems occur.

Data Science 82

Data Science Enterprise Experimentation Modeling 82

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization is a business capability where an organization can create and realize value from data and artificial intelligence (AI) assets. A value exchange system built on data products can drive business growth for your organization and gain competitive advantage.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

Domino Data Lab

AUGUST 6, 2021

Data science is an incredibly complex field. Framing data science projects within the four steps of the data science lifecycle (DSLC) makes it much easier to manage limited resources and control timelines, while ensuring projects meet or exceed the business requirements they were designed for.

Data Science 75

Data Science Testing Modeling Publishing 75

AWS Big Data

MAY 4, 2023

Welcome to the era of data. The sheer volume of data captured daily continues to grow, calling for platforms and solutions to evolve. The Amazon Sustainability Data Initiative (ASDI) uses the capabilities of Amazon S3 to provide a no-cost solution for you to store and share climate science workloads across the globe.

Data Processing 122

Data Processing Metadata Informatics Interactive 122

DataRobot Blog

JULY 21, 2022

Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. Assess the infrastructure.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. The Importance of Exploratory Analytics in the Data Science Lifecycle. Exploratory analysis is a critical component of the data science lifecycle. For one, Python remains the leading language for data science research.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Domino Data Lab

AUGUST 6, 2021

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. The complexity of models, and general limitations of expertise with data science among business leaders, creates an environment ripe for risk. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Birst BI

AUGUST 23, 2018

However, there are simply not enough data scientists in the world to deliver on the AI potential. Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. The Outsourcing of Data Science Functions.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Domino Data Lab

JULY 28, 2021

The data science lifecycle (DLSC) has been defined as an iterative process that leads from problem formulation to exploration, algorithmic analysis and data cleaning to obtaining a verifiable solution that can be used for decision making. Like any lifecycle, these stages are all interdependent. Manage Stage.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

AWS Big Data

JULY 28, 2023

The GDPR (General Data Protection Regulation) right to be forgotten, also known as the right to erasure, gives individuals the right to request the deletion of their personally identifiable information (PII) data held by organizations. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud.

Snapshot 98

Snapshot Metadata Measurement Data Warehouse 98

AWS Big Data

AUGUST 14, 2023

This post is the first in a series dedicated to the art and science of practical data mesh implementation (for an overview of data mesh, read the original whitepaper The data mesh shift ). Taken together, the posts in this series lay out some possible operating models for data mesh within an organization.

Management 98

Management Risk Measurement Optimization 98

IBM Big Data Hub

OCTOBER 20, 2023

AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually. Some AI platforms also provide advanced AI capabilities, such as natural language processing (NLP) and speech recognition. What types of features do AI platforms offer?

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

IBM Big Data Hub

AUGUST 11, 2023

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

Anmut

MARCH 22, 2023

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Organisations that reach the highest stage of data maturity achieve a market value increase of up to 500%, compared to lower maturity organisations.

Measurement 52

Measurement Modeling Data Quality Data Governance 52

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program? Establishing a solid vision and mission is key.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

IBM Big Data Hub

FEBRUARY 22, 2024

A recent IBM survey found that the top barriers preventing successful AI deployment include limited AI skills and expertise, data complexity, and ethical concerns. AI tools are now utilized in national security and to help protect against data breaches and cyberattacks. But AI also supports other strategic goals of the DoD.

Metadata 91

Metadata Measurement Risk Modeling 91

Jet Global

NOVEMBER 25, 2024

In the spirit of staying the course, here’s what Microsoft Dynamics users can expect as Microsoft continues investing resources into smart data management, security, and cloud computing solutions in the coming year. Its robust data security framework ensures the financial data used within Atlas is secure.

Reporting 52

Reporting Finance Dashboards Cost-Benefit 52

CIO Business Intelligence

APRIL 3, 2025

The traditional approaches for implementing AI have focused on AI chatbots, single declarative agents or synchronous processes. More activities come into play, including business logic and workflows, natural language, machine learning, data management, security, monitoring and more. This process requires careful planning.

Testing 117

Testing Metrics Measurement Cost-Benefit 117

CIO Business Intelligence

FEBRUARY 5, 2025

Digital transformation is not just about adopting new tools but also about reshaping business processes, culture and customer experiences to meet the evolving demands of the digital age. A typical lifecycle in the cloud adoption journey. One of the most significant enablers of digital transformation is cloud computing. Hybrid cloud.

IT 89

IT Cost-Benefit Digital Transformation Optimization 89

CIO Business Intelligence

APRIL 1, 2025

AI services require high resources like CPU/GPU and memory and hence cloud providers like Amazon AWS, Microsoft Azure and Google Cloud provide many AI services including features for genAI. By leveraging granular cost data, organizations can identify cost drivers, allocate expenses accurately and make informed financial decisions.

Forecasting 59

Forecasting Predictive Analytics Optimization Strategy 59

CIO Business Intelligence

MARCH 18, 2025

Information risk management is no longer a checkpoint at the end of development but must be woven throughout the entire software delivery lifecycle. Security is no longer expressed as a gate at the end of development but as an integral part of the entire delivery process. 2025 Banking Regulatory Outlook, Deloitte The stakes are clear.

Risk Management 99

Risk Management Risk Management Metrics 99