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. DataOps ensures that the data retrieved is relevant, high-quality, and up-to-date.

Data Quality 117

Data Quality Unstructured Data Testing Modeling 117

Cloudera

JULY 15, 2021

Across the industry, the pandemic caused a huge breakdown in model performance due to the change in macroeconomic conditions and government stimulus packages. Modeling that was previously well established – for both commercial and consumer lines – became less reliable. Low Probability, High Impact Events Readiness.

Risk 97

Risk Optimization Management Insurance 97

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. Just-in-Time” manufacturing increases production while optimizing resources.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

APRIL 16, 2024

While warp speed is a fictional concept, it’s an apt way to describe what generative AI (GenAI) and large language models (LLMs) are doing to exponentially accelerate Industry 4.0. By leveraging a GenAI-fueled edge with small language models (SLMs), this lengthy work will be streamlined and simplified. Data quality dependence.

Manufacturing 142

Manufacturing Digital Transformation Risk Dashboards 142

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. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models?

Measurement 52

Measurement Modeling Data Quality Data Governance 52

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 137

Data Lake Consulting Uncertainty Risk 137

IBM Big Data Hub

MAY 9, 2023

Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. Building a model requires specialized, hard-to-find skills — and each new task requires repeating the process. ” These large models have lowered the cost and labor involved in automation.

Enterprise 131

Enterprise Technology Modeling Cost-Benefit 131

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

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 259

Machine Learning Data Quality Statistics Modeling 259

Laminar Security

DECEMBER 1, 2023

DSPM is a term coined by Gartner to describe solutions that focus on discovering, classifying, and protecting sensitive data in cloud environments. DSPM solutions help organizations achieve data security compliance, reduce data breach risks, optimize cloud costs, and improve data quality, all while enabling data-driven innovation.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

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

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

JANUARY 22, 2024

Since the introduction of ChatGPT, the healthcare industry has been fascinated by the potential of AI models to generate new content. While the average person might be awed by how AI can create new images or re-imagine voices, healthcare is focused on how large language models can be used in their organizations.

Unstructured Data 96

Unstructured Data Digital Transformation Data Strategy Modeling 96

O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. You must detect when the model has become stale, and retrain it as necessary. The guardrail metric is a check to ensure that an AI doesn’t make a “mistake.”

Marketing 362

Marketing Experimentation Metrics Testing 362

Paul Turley

DECEMBER 13, 2018

At the heart of every a Business Intelligence reporting solution is a data model, to optimize queries and enable ad hoc report interactions. Data modeling technology has evolved quite a lot over the past 20 years or so. In the past, choices were simpler.

Modeling 40

Modeling Data Quality Business Intelligence Interactive 40

IBM Big Data Hub

NOVEMBER 21, 2023

A schema describes the structure of data. Optimize your Kafka environment by using a schema registry. A schema registry is essentially an agreement of the structure of your data within your Kafka environment. A schema registry also validates evolution of schemas. What’s next?

Data Quality 101

Data Quality Metadata Data-driven Optimization 101

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 results in optimized resource utilization and cost efficiencies while enhancing overall productivity.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

Smart Data Collective

APRIL 5, 2022

You will also want to know how to harvest the data that you get. Do an Overcast Survey to Ensure You Get Reliable Data. We have talked extensively about the importance of both data quality and data quantity. You have to ensure that you have quality assurance protocols baked into your data collection methodologies.

Data Collection 107

Data Collection Data Quality Big Data Data-driven 107

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 83

Metrics Machine Learning Risk Statistics 83

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 4, 2024

Like other CIOs, Katrina Redmond has been inundated with opportunities to deploy AI that promise to speed business and operations processes, and optimize workflows. The cost of implementing and running AI models can be quite high, so you have to be really careful in assessing the business worthiness of AI use cases,” he says.

Enterprise 134

Enterprise Cost-Benefit Forecasting Sales 134

IBM Big Data Hub

NOVEMBER 24, 2023

While rebuild results in maximum benefit, there is a need for high degree of investment, whereas rehost is about moving applications and data as such to cloud without any optimization and this requires less investments while value is low. We will explore key areas of acceleration with an example in this article.

Cost-Benefit 94

Cost-Benefit Testing Data-driven Enterprise 94

Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Ontotext

JANUARY 29, 2024

These will include developing a better understanding of AI, recognizing the role semantic metadata plays in data fabrics, and the rapid acceleration and adoption of knowledge graphs — which will be driven by large language models (LLMs) and the convergence of labeled property graphs (LPGs) and resource description frameworks (RDFs).

Strategy 52

Strategy Management Metadata Data-driven 52

IBM Big Data Hub

MAY 8, 2023

Technological risk—security AI algorithms are the parameters that optimizes the training data that gives the AI its ability to give insights. Should the parameters of an algorithm be leaked, a third party may be able to copy the model, causing economic and intellectual property loss to the owner of the model.

Insurance 71

Insurance Risk Testing Data Quality 71

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Alation

OCTOBER 5, 2021

The main reasons that a company’s data strategy and governance protocols fail to deliver are somewhat universal, regardless of the industry sector. Without a doubt, no company can achieve lasting profitability and sustainable growth with a poorly constructed data governance methodology. Picking the Right Data Governance Tools.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. For example, McKinsey estimates enterprises can cut 15% to 20% of cloud costs through optimizations, and implementing finops practices is one opportunity.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

IBM Big Data Hub

DECEMBER 20, 2023

Whether it’s deeper data analysis, optimization of business processes or improved customer experiences , having a well-defined purpose and plan will ensure that the adoption of AI aligns with the broader business goals. A model represents what was learned by a machine learning algorithm. What is an AI strategy?

Strategy 74

Strategy Business Objectives Cost-Benefit Consulting 74

IBM Big Data Hub

APRIL 25, 2024

This reality means that every brand in every industry with every business model needs to optimize the commerce experience, and thus the customer experience , to drive conversion rates and revenues. To ensure the success of this approach, it is crucial to maintain a strong focus on data quality, security and ethical considerations.

Strategy 87

Strategy Sales Marketing Consulting 87

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 25, 2022

But despite all the money flowing into ML projects, most organizations are struggling to get their ML models and applications working on production systems. . And another recent survey has the worst numbers of all, finding that 90% of ML models are not deployed to production. So what’s the problem? The problem with ML. research.

Machine Learning 133

Machine Learning Enterprise Deep Learning Cost-Benefit 133

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

CIO Business Intelligence

JUNE 9, 2023

Data d ependenc y Regardless of your industry, data is central to almost every business today. Leveraging that data, in AI models, for example, depends entirely on the accessibility, quality, granularity, and latency of your organization’s data. Consider wind turbine operation.

Strategy 115

Strategy Management Key Performance Indicator ROI 115

DataKitchen

MARCH 16, 2023

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Andrew White

MAY 4, 2020

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. As a result, Data, Analytics and AI are in even greater demand. In the realm of AI and Machine Leaning, data is used to train models to help explore specific business issues or questions.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90