O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. The model and the data specification become more important than the code.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

CIO Business Intelligence

FEBRUARY 26, 2025

We actually started our AI journey using agents almost right out of the gate, says Gary Kotovets, chief data and analytics officer at Dun & Bradstreet. The knowledge management systems are up to date and support API calls, but gen AI models communicate in plain English. Thats what Cisco is doing.

IT 141

IT Enterprise Interactive Data Quality 141

AWS Big Data

NOVEMBER 22, 2024

Now, with support for dbt Cloud, you can access a managed, cloud-based environment that automates and enhances your data transformation workflows. This upgrade allows you to build, test, and deploy data models in dbt with greater ease and efficiency, using all the features that dbt Cloud provides.

Data Lake 104

Data Lake Data Warehouse Cost-Benefit Data Transformation 104

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

Enterprise 342

Enterprise Testing Modeling Reporting 342

CIO Business Intelligence

FEBRUARY 6, 2025

The hype around large language models (LLMs) is undeniable. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. In life sciences, simple statistical software can analyze patient data.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

datapine

APRIL 15, 2020

Working software over comprehensive documentation. Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority. Finalize documentation, where necessary.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

DataKitchen

MAY 7, 2024

DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certificatio n (3 hours, online, free, signup online): DataOps Manifesto (over 30,000 signatures) One (..)

Data Quality 161

Data Quality Testing Consulting Metrics 161

CIO Business Intelligence

DECEMBER 11, 2024

Digital transformation started creating a digital presence of everything we do in our lives, and artificial intelligence (AI) and machine learning (ML) advancements in the past decade dramatically altered the data landscape. Implementing ML capabilities can help find the right thresholds.

Management 111

Management Data Governance Data Science Reporting 111

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 314

Management Machine Learning Metrics Modeling 314

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 279

Machine Learning Software Metadata Testing 279

AWS Big Data

APRIL 8, 2025

We will explore Icebergs concurrency model, examine common conflict scenarios, and provide practical implementation patterns of both automatic retry mechanisms and situations requiring custom conflict resolution logic for building resilient data pipelines. This scenario applies to any type of updates on an Iceberg table.

Snapshot 139

Snapshot Management Metadata Big Data 139

CIO Business Intelligence

JANUARY 30, 2025

While there is a lot of effort and content that is now available, it tends to be at a higher level which will require work to be done to create a governance model specifically for your organization. Governance is action and there are many actions an organization can take to create and implement an effective AI governance model.

Testing 93

Testing Metrics Cost-Benefit Modeling 93

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. The insights are used to produce informative content for stakeholders (decision-makers, business users, and clients).

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

Ontotext

MAY 26, 2021

In natural language processing (NLP) and computational linguistics the Gold Standard typically represents a corpus of text or a set of documents, annotated or tagged with the desired results for the analysis – be it designation of the corresponding part of speech, syntactic parsing, concept or relationship.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

CIO Business Intelligence

SEPTEMBER 12, 2024

The main reason is that it is difficult and time-consuming to consolidate, process, label, clean, and protect the information at scale to train AI models. An aircraft engine provider uses AI to manage thousands of technical documents required for engine certification, reducing administration time from 3-6 months to a few weeks.

Unstructured Data 119

Unstructured Data Data Quality Structured Data Machine Learning 119

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

CIO Business Intelligence

JUNE 5, 2024

Crucial data resides in hundreds of emails sent and received every day, on spreadsheets, in PowerPoint presentations, on videos, in pictures, in reports with graphs, in text documents, on web pages, in purchase orders, in utility bills, and on PDFs. That data is free flowing and does not reside in one place.

Management 142

Management Strategy Data Strategy Marketing 142

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

CIO Business Intelligence

JUNE 12, 2024

To help alleviate the complexity and extract insights, the foundation, using different AI models, is building an analytics layer on top of this database, having partnered with DataBricks and DataRobot. Some of the models are traditional machine learning (ML), and some, LaRovere says, are gen AI, including the new multi-modal advances.

Modeling 140

Modeling Testing Cost-Benefit Metadata 140

erwin

MARCH 21, 2019

With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Historically, BPM didn’t necessarily have to be tied to an organization’s data governance initiative. Choosing a BPM Tool: An Overview. Silo Buster.

Modeling 75

Modeling Metadata Data Governance IT 75

Smart Data Collective

SEPTEMBER 26, 2021

Data visualization enables you to: Make sense of the distributional characteristics of variables Easily identify data entry issues Choose suitable variables for data analysis Assess the outcome of predictive models Communicate the results to those interested. The central concept is the idea of a document.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

erwin

JANUARY 3, 2020

While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping into the true value of data as the foundation of the digital business model. Data Modeling: Drive Business Value and Underpin Governance with an Enterprise Data Model.

Data Governance 139

Data Governance Digital Transformation IoT Metadata 139

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

SEPTEMBER 10, 2024

This AI-augmented approach ensures that no critical feature falls through the cracks and that accurate requirements documents reduce the likelihood of defects. Invest in data quality: GenAI models are only as good as the data they’re trained on -with GenAI, mistakes can be amplified at speed.

Software 124

Software Digital Transformation Testing Advertising 124

CIO Business Intelligence

MAY 2, 2023

Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria. One recent study shows that only 50% follow a product-centric operating model focusing on customer centricity and delivering delightful customer experiences.

Digital Transformation 141

Digital Transformation IT Data-driven Data Quality 141

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. We look at the entire landscape of information that an enterprise has,” Sangani said. “As

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Map data flows.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

CIO Business Intelligence

AUGUST 14, 2024

It’s embedded in the applications we use every day and the security model overall is pretty airtight. Microsoft has also made investments beyond OpenAI, for example in Mistral and Meta’s LLAMA models, in its own small language models like Phi, and by partnering with providers like Cohere, Hugging Face, and Nvidia. That’s risky.”

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

DataRobot Blog

DECEMBER 15, 2022

Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning. Prepare your data for Time Series Forecasting. Configuring an ML project. Settings for Time Series projects.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

CIO Business Intelligence

JANUARY 15, 2024

With seven operating centers, nine research facilities, and more than 18,000 staff, the agency continually generates an overwhelming amount of data, which it stores in more than 30 science data repositories across five topical areas — astrophysics, heliophysics, biological science, physical science, earth science, and planetary science.

Informatics 131

Informatics Metadata Data mining Digital Transformation 131

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Organizations still depend too much on manual data management.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110