Dataversity

APRIL 22, 2024

So why are many technology leaders attempting to adopt GenAI technologies before ensuring their data quality can be trusted? Reliable and consistent data is the bedrock of a successful AI strategy.

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Smart Data Collective

SEPTEMBER 29, 2022

Every company deals with a certain number of documents on a daily basis: invoices, receipts, logistics, or HR documents… You have to keep these documents, extract the useful information for your business, and then integrate them manually into your database. The software extracts all the information in plain text in a TXT format.

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Dataversity

NOVEMBER 6, 2023

This is my monthly check-in to share with you the people and ideas I encounter as a data evangelist with DATAVERSITY. This month we’re talking about Data Quality (DQ). Read last month’s column here.)

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Data Quality Data Governance 119

Flipboard

JUNE 5, 2023

True data quality simplification requires transformation of both code and data, because the two are inextricably linked. Code sprawl and data siloing both imply bad habits that should be the exception, rather than the norm.

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Data Quality Data Silos Big Data Big Data 121

Flipboard

MARCH 13, 2023

Presented by BMC Poor data quality costs organizations an average $12.9 Organizations are beginning to recognize that not only does it have a direct impact on revenue over the long term, but poor data quality also increases the complexity of data ecosystems, and directly impacts the … million a year.

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Dataversity

OCTOBER 25, 2023

In fact, it’s been more than three decades of innovation in this market, resulting in the development of thousands of data tools and a global data preparation tools market size that’s set […] The post Why Is Data Quality Still So Hard to Achieve? appeared first on DATAVERSITY.

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Data Quality Data Preparation Algorithm Data Silos 104

Flipboard

JUNE 15, 2023

Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses …

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Data Quality Data Engineering Data Engineer Data Engineering 149

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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Precisely

SEPTEMBER 9, 2024

Key Takeaways: • Implement effective data quality management (DQM) to support the data accuracy, trustworthiness, and reliability you need for stronger analytics and decision-making. Embrace automation to streamline data quality processes like profiling and standardization. What is Data Quality Management (DQM)?

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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

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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Database Natural Language Processing AI AI 277

Precisely

JANUARY 15, 2024

When you delve into the intricacies of data quality, however, these two important pieces of the puzzle are distinctly different. Knowing the distinction can help you to better understand the bigger picture of data quality. What Is Data Validation? For a list of addresses that includes countries outside the U.S.,

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IBM Data Science in Practice

APRIL 26, 2024

Metadata Enrichment: Empowering Data Governance Data Quality Tab from Metadata Enrichment Metadata enrichment is a crucial aspect of data governance, enabling organizations to enhance the quality and context of their data assets. This dataset spans a wide range of ages, from teenagers to senior citizens.

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Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence.

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Data Science Dojo

JULY 30, 2024

The relentless tide of data preserve—customer behavior, market trends, and hidden insights—all waiting to be harnessed. They ignore the call of data analytics, forsaking efficiency, ROI, and informed decisions. Meanwhile, their rivals ride the data-driven wave, steering toward success.

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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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Data Science Blog

AUGUST 22, 2024

This shift not only saves time but also ensures a higher standard of data quality. Tools like BiG EVAL are leading data quality field for all technical systems in which data is transported and transformed. Foster a Data-Driven Culture Promote a culture where data quality is a shared responsibility.

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Dataconomy

APRIL 17, 2024

Everything from lending platforms to prediction markets relies on reliable and timely information from oracles, which link the blockchain with real-world data. A lack of genuine decentralization is at the heart of the problem, as it leaves data susceptible to manipulation and inaccurate results when relied upon by only a few sources.

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Data Quality 172

Tableau

OCTOBER 7, 2024

Lineage and data health: We will enhance data details and data lineage in Tableau Catalog by allowing dbt to import key data health information, such as when data was last refreshed, when data quality checks passed, and more.

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Tableau Data Quality Analytics Analytics 137

IBM Data Science in Practice

DECEMBER 7, 2022

IBM Multicloud Data Integration helps organizations connect data from disparate sources, build data pipelines, remediate data issues, enrich data, and deliver integrated data to multicloud platforms where it can easily accessed by data consumers or built into a data product.

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Data Science Dojo

SEPTEMBER 6, 2023

Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information. Data ownership extends beyond mere possession—it involves accountability for data quality, accuracy, and appropriate use.

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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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Data Science Dojo

MARCH 24, 2023

This includes ensuring that data is properly labeled and processed, managing data quality, and ensuring that the right data is used for training and testing models. Collaboration and Communication: Collaboration and communication between data scientists, engineers, and other stakeholders is essential for successful MLOps.

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Data Science Dojo

MARCH 24, 2023

This includes ensuring that data is properly labeled and processed, managing data quality, and ensuring that the right data is used for training and testing models. Here are some of the key advantages: Advantages of ML Ops – Data Science Dojo 1.

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Smart Data Collective

SEPTEMBER 28, 2022

A data management solution helps your business run more efficiently by making sure that your data is reliable and secure. You can use information management software to improve your decision-making process and ensure that you’re compliant with the law. Data management helps you comply with the law.

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Smart Data Collective

DECEMBER 21, 2022

Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. One of the biggest issues pertains to data quality.

Analytics 123

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Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

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IBM Data Science in Practice

NOVEMBER 28, 2022

IBM Multicloud Data Integration helps organizations connect data from disparate sources, build data pipelines, remediate data issues, enrich data, and deliver integrated data to multicloud platforms where it can easily accessed by data consumers or built into a data product.

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Data Pipeline Data Quality Data Preparation Data Governance 130

Hacker News

JUNE 14, 2024

Navigating Nemotron to Generate Synthetic Data LLMs can help developers generate synthetic training data in scenarios where access to large, diverse labeled datasets is limited. Then, to boost the quality of the AI-generated data, developers can use the Nemotron-4 340B Reward model to filter for high-quality responses.

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Flipboard

JUNE 15, 2023

Read the full series here: Building the foundation for customer data quality. This article is part of a VB special issue. The rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies is pushing the boundaries of what can be achieved in marketing, customer experience …

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Precisely

SEPTEMBER 19, 2024

Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications.

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Dataversity

SEPTEMBER 25, 2023

In an era where large language models (LLMs) are redefining AI digital interactions, the criticality of accurate, high-quality, and pertinent data labeling emerges as paramount. That means data labelers and the vendors overseeing them must seamlessly blend data quality with human expertise and ethical work practices.

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Data Quality AI AI Data Governance 104

Data Science Dojo

JULY 5, 2024

TensorFlow There are three main types of TensorFlow frameworks for testing: TensorFlow Extended (TFX): This is designed for production pipeline testing, offering tools for data validation, model analysis, and deployment. TensorFlow Data Validation: Useful for testing data quality in ML pipelines.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

To quickly explore the loan data, choose Get data insights and select the loan_status target column and Classification problem type. The generated Data Quality and Insight report provides key statistics, visualizations, and feature importance analyses. Now you have a balanced target column.

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Data Science Dojo

OCTOBER 10, 2023

Link to event -> Generative AI and Data Storytelling Here are some of the key takeaways from the article: Generative AI is a type of artificial intelligence that can create new content, such as text, images, and music. Data storytelling is the process of using data to communicate a story in a way that is engaging and informative.

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Precisely

SEPTEMBER 25, 2023

Defining Data Validation and Enrichment Processes Before we explore the benefits of data validation and enrichment and how these processes support the data you need for powerful decision-making, let’s define each term. Think of address data, for example. Is there missing information? Let’s explore.

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AWS Machine Learning Blog

DECEMBER 15, 2023

Without creating and maintaining data pipelines, you will be able to power ML models with your unstructured data stored in Amazon DocumentDB. Your mobile app stores information about restaurants in Amazon DocumentDB because of its scalability and flexible schema capabilities. For more information, see Add model access.

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