Flipboard

MAY 5, 2025

When it comes to dealing with data quality, teams and companies fall into one of three modes: unmanaged, organized cleanup, or proactive

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Data Quality Analytics Analytics Computer Science 137

AWS Machine Learning Blog

JANUARY 15, 2025

The solution is designed to provide customers with a detailed, personalized explanation of their preferred features, empowering them to make informed decisions. Requested information is intelligently fetched from multiple sources such as company product metadata, sales transactions, OEM reports, and more to generate meaningful responses.

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Data Science Blog

OCTOBER 1, 2024

Just like a skyscraper’s stability depends on a solid foundation, the accuracy and reliability of your insights rely on top-notch data quality. Enter Generative AI – a game-changing technology revolutionizing data management and utilization. Businesses must ensure their data is clean, structured, and reliable.

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Dataconomy

APRIL 8, 2022

Organizations can effectively manage the quality of their information by doing data profiling. Businesses must first profile data metrics to extract valuable and practical insights from data. Data profiling is becoming increasingly essential as more firms generate huge quantities of data every day.

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Data Profiling Data Quality Big Data Big Data 190

Dataconomy

JUNE 10, 2025

Understanding the complexities of noisy data is essential for improving data quality and enhancing the outcomes of predictive algorithms. What is noisy data? Noisy data pertains to irrelevant, erroneous, or misleading information that can hinder data clarity and integrity.

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Data Quality Data Analysis Data Analysis Machine Learning 91

Dataconomy

JUNE 10, 2025

Data availability is a critical concept in today’s digital landscape. As organizations increasingly depend on data for decision-making and operations, ensuring that this information is readily accessible becomes paramount. Data quality issues The integrity of data is crucial for availability.

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Data Quality 91

Dataconomy

NOVEMBER 12, 2024

“Some researchers at the company believe Orion isn’t reliably better than its predecessor in handling certain tasks,” reported The Information. Researchers have found that relying heavily on synthetic data can cause models to degrade over time.

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Dataversity

MARCH 26, 2025

Unreliable or outdated data can have huge negative consequences for even the best-laid plans, especially if youre not aware there were issues with the data in the first place. Thats why data observability […] The post Implementing Data Observability to Proactively Address Data Quality Issues appeared first on DATAVERSITY.

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Data Observability Data Quality Data Governance 69

Dataconomy

JUNE 3, 2025

Data citizens play a pivotal role in transforming how organizations leverage information. These individuals are not mere data users; they embody a shift in the workplace culture, where employees actively participate in data-driven decision-making.

Data Governance 91

Data Governance Business Intelligence Business Intelligence Data Quality 91

Dataversity

APRIL 3, 2025

This is the first in a two-part series exploring Data Quality and the ISO 25000 standard. Despite efforts to recall the bombers, one plane successfully drops a […] The post Mind the Gap: Did You Know About the ISO 25000 Series Data Quality Standards? Ripper orders a nuclear strike on the USSR.

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Data Quality Data Governance 52

Dataconomy

JUNE 11, 2025

Role of data governance Data governance is crucial for fostering an environment where data usage is responsible and compliant with regulations. Governance policies establish standards for data quality, ensuring that analytics outcomes are reliable and actionable.

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Data Science Dojo

JANUARY 25, 2024

The data points in the three-dimensional space can capture the semantic relationships and contextual information associated with them. With the advent of generative AI, the complexity of data makes vector embeddings a crucial aspect of modern-day processing and handling of information.

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Dataversity

MAY 1, 2025

This is the second in a two-part series exploring data quality and the ISO 25000 standard. You recognize that having quality data is important for accurate AI models. Youre with the program.

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Data Quality AI AI Data Governance 59

Dataconomy

APRIL 21, 2023

Data fidelity, the degree to which data can be trusted to be accurate and reliable, is a critical factor in the success of any data-driven business. Companies are collecting and analyzing vast amounts of data to gain insights into customer behavior, identify trends, and make informed decisions.

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Data Quality Data Governance Data Visualization Power BI 182

Dataconomy

MARCH 17, 2025

Augmented analytics is revolutionizing how organizations interact with their data. By harnessing the power of machine learning (ML) and natural language processing (NLP), businesses can streamline their data analysis processes and make more informed decisions. This leads to better business planning and resource allocation.

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Dataconomy

JUNE 10, 2025

Data analytics serves as a powerful tool in navigating the vast ocean of information available today. Organizations across industries harness the potential of data analytics to make informed decisions, optimize operations, and stay competitive in the ever-changing marketplace. What is data analytics?

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Analytics Analytics Big Data Analytics Big Data Analytics 91

Dataconomy

NOVEMBER 11, 2024

This approach is ideal for use cases requiring accuracy and up-to-date information, like providing technical product documentation or customer support. For instance, prompts like “Provide a detailed but informal explanation” can shape the output significantly without requiring the model itself to be fine-tuned.

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Data Preparation Database Data Quality Machine Learning 203

Precisely

JANUARY 9, 2025

Each source system had their own proprietary rules and standards around data capture and maintenance, so when trying to bring different versions of similar data together such as customer, address, product, or financial data, for example there was no clear way to reconcile these discrepancies. A data lake!

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Data Warehouse Hadoop Data Lakes Data Governance 119

Precisely

JANUARY 30, 2025

Recognize that artificial intelligence is a data governance accelerator and a process that must be governed to monitor ethical considerations and risk. Integrate data governance and data quality practices to create a seamless user experience and build trust in your data.

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Data Science Dojo

SEPTEMBER 15, 2023

While there’s no denying that large language models can generate false information, we can take action to reduce the risk. Large Language Models (LLMs), such as OpenAI’s ChatGPT, often face a challenge: the possibility of producing inaccurate information. AI hallucinations: When language models dream in algorithms.

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AI AI Data Quality Algorithm 365

Dataconomy

JUNE 11, 2025

A data clean room is a secure environment designed to protect user privacy while enabling interaction between advertising providers and content platforms. These rooms allow organizations to analyze data collaboratively without exposing sensitive individual information.

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Dataconomy

APRIL 17, 2025

Enhancing model accuracy and decision making Effectively using PSI not only refines predictive accuracy but also informs strategic business decisions. Data quality assurance PSI acts as a validation measure for data quality, particularly beneficial in environments reliant on automated data collection processes.

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Data Quality Analytics Analytics 91

Data Science Dojo

MARCH 18, 2024

Yet, despite these impressive capabilities, their limitations became more apparent when tasked with providing up-to-date information on global events or expert knowledge in specialized fields. Revisit the best large language models of 2023 Enter RAG and finetuning RAG revolutionizes the way language models access and use information.

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Dataconomy

JUNE 3, 2025

Data integrity is a critical component of effective data management, essential for maintaining trust and accuracy in digital information. As organizations increasingly rely on data for decision-making and operational efficiency, ensuring that this data remains intact and accessible only to authorized personnel becomes paramount.

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Data Quality Data Analysis Data Analysis Analytics 91

Dataconomy

MARCH 20, 2025

Unlike a data warehouse that serves the entire organization, a data mart focuses on a single subject area, making it easier for departments to access relevant information without navigating extensive datasets. This process extracts data from various sources, transforms it into a desired format, and loads it into the data mart.

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Data Warehouse ETL Data Quality Database 91

Dataconomy

JUNE 4, 2025

Data ingestion is a crucial process in handling vast amounts of information that organizations generate and interact with daily. It encompasses various methods to collect, process, and utilize data. What is data ingestion? Each type caters to different data processing requirements and operational objectives.

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ETL Data Quality Data Warehouse Analytics 91

Dataconomy

MARCH 29, 2025

You need to provide the user with information within a short time frame without compromising the user experience. He cited delivery time prediction as an example, where each user’s data is unique and depends on numerous factors, precluding pre-caching. Data management is another critical area.

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Flipboard

NOVEMBER 22, 2024

It serves as the hub for defining and enforcing data governance policies, data cataloging, data lineage tracking, and managing data access controls across the organization. Data lake account (producer) – There can be one or more data lake accounts within the organization.

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Precisely

JUNE 10, 2025

Key takeaways: New Data Integrity Suite innovations include AI-powered data quality, and new data observability, lineage, location intelligence, and enrichment capabilities. If you’re navigating growing data complexity, rising expectations, and pressure to innovate faster, you’re not alone.

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Analytics Analytics Data Quality AI 52

Dataconomy

MARCH 13, 2025

However, for AI to provide reliable recommendations, it requires structured, high-quality data and thats where the real challenge begins. A significant portion of critical patient information is buried in free-text doctors notes, scattered across multiple hospital systems, or entirely undocumented. Medical records are messy.

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AI AI Natural Language Processing Artificial Intelligence 103

Dataversity

JUNE 5, 2025

We are at the threshold of the most significant changes in information management, data governance, and analytics since the inventions of the relational database and SQL. At the core, though, little has changed.The basic […] The post Mind the Gap: AI-Driven Data and Analytics Disruption appeared first on DATAVERSITY.

Analytics 96

Analytics Analytics Data Governance SQL 96

Dataversity

JANUARY 31, 2025

Data Sips is a new video miniseries presented by Ippon Technologies and DATAVERSITY that showcases quick conversations with industry experts from last months Data Governance & Information Quality (DGIQ) Conference in Washington, D.C.

Data Governance 52

Data Governance Data Quality 52

AWS Machine Learning Blog

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. Prepare the data to build your model training pipeline.

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Precisely

JANUARY 27, 2025

That number jumps to 60% when asked specifically about obstacles to AI readiness, making it clear that the scarcity of skilled professionals makes it difficult for organizations to fully capitalize on their data assets and implement effective AI solutions. In fact, its second only to data quality. Youre not alone.

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Data Quality Data Governance Analytics Analytics 59

Machine Learning Research at Apple

FEBRUARY 19, 2025

Foundation models are trained on large-scale web-crawled datasets, which often contain noise, biases, and irrelevant information. This motivates the use of data selection techniques, which can be divided into model-free variants -- relying on heuristic rules and downstream datasets -- and model-based, e.g., using influence functions.

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Data Quality 130

Flipboard

DECEMBER 27, 2023

Presented by SQream The challenges of AI compound as it hurtles forward: demands of data preparation, large data sets and data quality, the time sink of long-running queries, batch processes and more. In this VB Spotlight, William Benton, principal product architect at NVIDIA, and others explain how …

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Data Preparation Analytics Analytics Data Quality 181

Dataconomy

JUNE 3, 2025

Cold backups, or offline backups, play a pivotal role in data management by providing a reliable method for preserving essential information. In an era where data integrity is paramount, understanding the intricacies of cold backups helps organizations safeguard against data loss and inconsistencies.

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Database Data Quality 91