DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

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 259

Machine Learning Data Quality Statistics Modeling 259

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

APRIL 1, 2024

Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. You’ll also institute guardrails for data governance, data quality, data integrity, and data security. Right-size your model(s). Choose a workload location. 2024 Artificial Intelligence

Data Lake 130

Data Lake Consulting Uncertainty Risk 130

Ontotext

FEBRUARY 14, 2024

Data integration If your organization’s idea of data integration is printing out multiple reports and manually cross-referencing them, you might not be ready for a knowledge graph. There’s a famous saying by a statistician, George Box, “All models are wrong, but some are useful.”

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. And until recently, such governance processes have been fragmented.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

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 91

Data Governance Unstructured Data Metadata Data Lake 91

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

Insurance 176

Insurance Metadata Data-driven Data Quality 176

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 68

Data Quality Data Integration Metadata Cost-Benefit 68

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. It’s a huge productivity loss.”

Data-driven 52

Data-driven Strategy Sales Data Integration 52

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Initially, the infrastructure is unstable, but then we look at our source data and find many problems. Our customers start looking at the data in dashboards and models and then find many issues.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

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

APRIL 17, 2024

Salesforce’s reported bid to acquire enterprise data management vendor Informatica could mean consolidation for the integration platform-as-a-service (iPaaS) market and a new revenue stream for Salesforce, according to analysts.

Cost-Benefit 127

Cost-Benefit B2B Marketing Enterprise 127

DataKitchen

OCTOBER 2, 2023

One of the most pressing issues is the ownership of databases by multiple data teams, each with its governance protocols, leading to a volatile data environment rife with inconsistencies and errors. This lack of control is exacerbated by many people and/or automated data ingestion processes introducing changes to the data.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

IBM Big Data Hub

MAY 9, 2022

Others have come into sharper focus relatively recently: a global effort to create new data privacy laws, a post-pandemic expectation by customers to know them individually across all touchpoints, and increased attention on any racial, gender-based, or socioeconomic bias in AI models. Multicloud data integration.

Management 56

Management Data Quality Metadata Data Integration 56

CIO Business Intelligence

JANUARY 24, 2024

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

IBM Big Data Hub

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Data Governance 57

Data Governance Enterprise Modeling Risk 57

DataKitchen

DECEMBER 9, 2022

DataOps involves close collaboration between data scientists, IT professionals, and business stakeholders, and it often involves the use of automation and other technologies to streamline data-related tasks. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

IBM Big Data Hub

JULY 6, 2022

Businesses of all sizes, in all industries are facing a data quality problem. 73% of business executives are unhappy with data quality and 61% of organizations are unable to harness data to create a sustained competitive advantage 1. Looking toward the future .

Metadata 56

Metadata Data Quality Snapshot Cost-Benefit 56

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

APRIL 29, 2022

Forward-thinking transformation leaders have realised that more focus needs to be placed on ‘data-centric value creation’ and have made this the pre-eminent organising principle in their organisations. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’ About Andrew P.

Data Governance 145

Data Governance IT Risk Data Lake 145

AWS Big Data

DECEMBER 21, 2023

OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration. Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue.

Analytics 92

Analytics IT Data Lake Visualization 92

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making. This resulted in increased profitability and strengthened competitive positioning within the industry.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

IBM Big Data Hub

JUNE 23, 2022

The ability to compose and re-use data services with IBM’s data fabric on IBM Cloud Pak for Data allows you to tackle a variety of use cases such as multi-cloud data integration, governance and privacy, customer 360, and MLOps and Trustworthy AI. Providing the semantic.

Enterprise 52

Enterprise Metadata Data Governance Machine Learning 52

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. They create reliable, consistent and communicable models for representing data. Schemas are powerful.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Data Virtualization

MARCH 7, 2024

One thing is clear; if data-centric organizations want to succeed in. The post Data Management Predictions for 2024: Five Trends appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 59

Management Data Integration Strategy Data Lake 59

Andrew White

DECEMBER 4, 2019

I argued that one vendors’ book on data quality was really about data governance; I argued that another vendors’ marketing message was totally upside down; and I argued that some approaches to achieving single source of truth were different from traditional approaches. See Salesforce acquisition of Tableau – What does it mean?

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. This provides a solid foundation for efficient data integration.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

CIO Business Intelligence

JANUARY 9, 2024

Can the current state of our data operations deliver the results we seek? Another tough topic that CIOs are having to surface to their colleagues: how problems with enterprise data quality stymie their AI ambitions. 1 among the top three risks — followed by statistical validity and model accuracy.

IT 129

IT Risk Cost-Benefit Enterprise 129

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Having disparate data sources housed in legacy systems can add further layers of complexity, causing issues around data integrity, data quality and data completeness.

Analytics 90

Analytics Insurance Big Data Uncertainty 90

Jedox

FEBRUARY 13, 2020

The power of artificial intelligence (AI) lies within its ability to make sense of large amounts of data. For the increasing support of planning, budgeting and controlling processes through advanced analytics and AI solutions, powerful data management and data integration are an indispensable prerequisite.

Forecasting 58

Forecasting Predictive Analytics Sales Data Integration 58

FineReport

MAY 31, 2023

Dupont Analysis Dashboard FineReport simplifies the implementation of the Dupont analysis model, enabling an in-depth examination of an enterprise’s financial condition through Return on Investment (ROI). The Dupont analysis model comprises three key components: profit margin, asset turnover, and equity multiplier.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Data Virtualization

JANUARY 25, 2024

One thing is clear; if data-centric organizations want to succeed in 2024, The post Data Management Predictions for 2024: Five Trends appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 59

Management Data Integration Strategy Data Lake 59