CIO Business Intelligence

DECEMBER 20, 2024

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Curate the data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

CIO Business Intelligence

OCTOBER 29, 2024

Likewise, compromised or tainted data can result in misguided decision-making, unreliable AI model outputs, and even expose a company to ransomware. Data exfiltration in an AI world It is undeniable at this point in time that the value of your enterprise data has risen with the growth of large language models and AI-driven analytics.

Enterprise 134

Enterprise Broadcasting Risk Sales 134

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. The problem is even more magnified in the case of structured enterprise data.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

CIO Business Intelligence

OCTOBER 9, 2024

How will organizations wield AI to seize greater opportunities, engage employees, and drive secure access without compromising data integrity and compliance? While it may sound simplistic, the first step towards managing high-quality data and right-sizing AI is defining the GenAI use cases for your business.

Strategy 143

Strategy Modeling Management Data Lake 143

erwin

JANUARY 9, 2020

Then there’s unstructured data with no contextual framework to govern data flows across the enterprise not to mention time-consuming manual data preparation and limited views of data lineage. Today’s data modeling is not your father’s data modeling software.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Analytics Vidhya

NOVEMBER 30, 2021

This article was published as a part of the Data Science Blogathon. Introduction to ETL ETL is a type of three-step data integration: Extraction, Transformation, Load are processing, used to combine data from multiple sources. It is commonly used to build Big Data.

Big Data 382

Big Data Data Science Data Integration Publishing 382

CIO Business Intelligence

NOVEMBER 19, 2024

The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both. Imagine that you’re a data engineer. The data is spread out across your different storage systems, and you don’t know what is where. What does the next generation of AI workloads need?

Management 116

Management Unstructured Data Deep Learning Metadata 116

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

Data Virtualization

OCTOBER 31, 2024

Reading Time: 2 minutes When making decisions that are critical to national security, governments rely on data, and those that leverage the cutting edge technology of generative AI foundation models will have a distinct advantage over their adversaries. Pros and Cons of generative AI.

Management 52

Management Modeling Data Integration Technology 52

O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Data Platforms. Data Integration and Data Pipelines.

Machine Learning 279

Machine Learning Enterprise IoT Big Data 279

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 problem is that, before AI agents can be integrated into a companys infrastructure, that infrastructure must be brought up to modern standards. Thats what Cisco is doing.

IT 141

IT Enterprise Interactive Data Quality 141

CIO Business Intelligence

FEBRUARY 27, 2025

Data professionals need to access and work with this information for businesses to run efficiently, and to make strategic forecasting decisions through AI-powered data models. Without integrating mainframe data, it is likely that AI models and analytics initiatives will have blind spots.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

O'Reilly on Data

OCTOBER 11, 2022

So from the start, we have a data integration problem compounded with a compliance problem. An AI project that doesn’t address data integration and governance (including compliance) is bound to fail, regardless of how good your AI technology might be. Data needs to become the means, a tool for making good decisions.

Data Integration 353

Data Integration Insurance Dashboards Data-driven 353

CIO Business Intelligence

DECEMBER 18, 2024

Instead, were witnessing a maturation of the industry, shifting towards more sustainable business models and a focus on profitability. SaaS pricing is evolving While SaaS isnt dead, traditional SaaS subscription models are being strongly and rightfully challenged. AI: Disruption or evolution?

ROI 116

ROI Software Finance Uncertainty 116

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

Bigeye’s anomaly detection capabilities rely on the automated generation of data quality thresholds based on machine learning (ML) models fueled by historical data. The company also offers associated alerts delivered to data owners and data consumers, and reinforcement learning to adapt notifications based on user feedback.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. To achieve this, EUROGATE designed an architecture that uses Amazon DataZone to publish specific digital twin data sets, enabling access to them with SageMaker in a separate AWS account.

IoT 110

IoT Machine Learning Metadata Data-driven 110

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration .

Testing 300

Testing Machine Learning Consulting Data Science 300

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 277

Machine Learning Risk Management Statistics 277

AWS Big Data

JULY 26, 2023

Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions. Are there recommended approaches to provisioning components for data integration?

Data Integration 94

Data Integration Snapshot Testing Visualization 94

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

AWS Big Data

DECEMBER 4, 2024

They’re taking data they’ve historically used for analytics or business reporting and putting it to work in machine learning (ML) models and AI-powered applications. Amazon SageMaker Unified Studio (Preview) solves this challenge by providing an integrated authoring experience to use all your data and tools for analytics and AI.

Data Analytics 100

Data Analytics Analytics Data Lake Data Quality 100

AWS Big Data

NOVEMBER 15, 2024

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment. Each table represents a single data store.

Metadata 115

Metadata Modeling Data-driven Machine Learning 115

AWS Big Data

MARCH 13, 2025

From within the unified studio, you can discover data and AI assets from across your organization, then work together in projects to securely build and share analytics and AI artifacts, including data, models, and generative AI applications.

Analytics 86

Analytics Data Lake Data Warehouse Data-driven 86

AWS Big Data

JULY 19, 2023

You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model. Amazon Redshift provides built-in features to accelerate the process of modeling, orchestrating, and reporting from a dimensional model. Declare the grain of your data.

Modeling 91

Modeling Sales Data Warehouse Snapshot 91

KDnuggets

JUNE 19, 2024

Perform data integrity tests and generate model evaluation reports by writing a few lines of code.

Testing 146

Testing Machine Learning Data Integration Reporting 146

CIO Business Intelligence

AUGUST 16, 2023

ChatGPT is capable of doing many of these tasks, but the custom support chatbot is using another model called text-embedding-ada-002, another generative AI model from OpenAI, specifically designed to work with embeddings—a type of database specifically designed to feed data into large language models (LLM).

Modeling 98

Modeling Enterprise Cost-Benefit Data Science 98

CIO Business Intelligence

JANUARY 21, 2025

Each product comes with its own licensing model, metering system, graphical user interface (GUI), and operational workflow. Extreme Networks has introduced Extreme Platform ONE, a platform that reduces the complexity for enterprises by seamlessly integrating AI-powered automation, networking, and security.

IT 98

IT IoT Interactive Enterprise 98

Data Virtualization

FEBRUARY 15, 2024

The post Data Integration: It’s not a Technological Challenge, but a Semantic Adventure appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 59

Data Integration Technology Risk Management 59

DataKitchen

MAY 14, 2024

Chris will overview data at rest and in use, with Eric returning to demonstrate the practical steps in data testing for both states. Session 3: Mastering Data Testing in Development and Migration During our third session, the focus will shift towards regression and impact assessment in development cycles. Reserve Your Spot!

Data Quality 195

Data Quality Testing Metrics Measurement 195

AWS Big Data

JANUARY 9, 2025

Simplified data corrections and updates Iceberg enhances data management for quants in capital markets through its robust insert, delete, and update capabilities. These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

O'Reilly on Data

FEBRUARY 11, 2019

Foundational data technologies. Machine learning and AI require data—specifically, labeled data for training models. Data lineage, data catalog, and data governance solutions can increase usage of data systems by enhancing trustworthiness of data. Data Platforms.

Big Data 271

Big Data Technology Machine Learning Deep Learning 271

AWS Big Data

DECEMBER 17, 2024

Seamless Lakehouse architectures Lakehouse brings together flexibility and openness of data lakes with the performance and transactional capabilities of data warehouses. Lakehouse allows you to use preferred analytics engines and AI models of your choice with consistent governance across all your data.

Data Lake 95

Data Lake Data Warehouse Data-driven Optimization 95

Data Virtualization

FEBRUARY 22, 2024

Reading Time: 6 minutes The emergence of Large Language Models (LLMs) and Generative AI marks a significant leap in technology, promising to deliver transformational automation and innovation across diverse industries and use cases. Having said that, as everyone races to develop next generation AI.

Modeling 69

Modeling Data Integration Management Technology 69

AWS Big Data

DECEMBER 4, 2024

From the Unified Studio, you can collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics. You can use a simple visual interface to compose flows that move and transform data and run them on serverless compute.

Visualization 115

Visualization Sales Data-driven Analytics 115

David Menninger's Analyst Perspectives

MAY 9, 2024

Large language models (LLMs) and generative AI (GenAI) have taken the AI world by storm. Our team has also described how AI can help enterprises improve customer experiences , transform human capital management , improve marketing and sales effectiveness , enhance data integration processes and drive automation for enhanced efficiency.

Finance 130

Finance Sales Data Integration Marketing 130

Cloudera

DECEMBER 4, 2024

introduces new features specifically designed to fuel GenAI initiatives: New AI Processors: Harness the power of cutting-edge AI models with new processors that simplify integration and streamline data preparation for GenAI applications. Accelerating GenAI with Powerful New Capabilities Cloudera DataFlow 2.9

Metrics 93

Metrics Data Integration Management Modeling 93