phData

AUGUST 5, 2024

Horizon addresses key aspects of data governance, including: Compliance Security Access Privacy Interoperability Throughout the remainder of this blog, we will dive deeper into each of the above components and take a look at the ways in which Horizon can help. Tag-Based Masking Policies : Mask columns automatically based on tags.

Data Governance 52

Data Governance Data Quality Data Lakes ML 52

Tableau

MARCH 21, 2023

Data discovery and trust have been core principles of Tableau Catalog since its very inception. Learn about the latest features to help users find trusted data at the right time, so they can consume the data with confidence.

Tableau 98

Tableau Data Analyst Data Quality Data Governance 98

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Tableau

MARCH 21, 2023

Data discovery and trust have been core principles of Tableau Catalog since its very inception. Learn about the latest features to help users find trusted data at the right time, so they can consume the data with confidence.

Tableau 52

Tableau Data Analyst Data Quality Data Governance 52

IBM Journey to AI blog

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. Data quality Data quality is essentially the measure of data integrity.

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Snorkel AI

FEBRUARY 2, 2023

Streamlined tagging workflows. Improved tagging analysis. Auto-generated tag-based LFs. Labeling function quality analysis. The label model outputs a large, probabilistic training data set that the platform can use to train a full ML model, which generalizes beyond the label model. Selecting tags in Snorkel Flow.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

FEBRUARY 2, 2023

Streamlined tagging workflows. Improved tagging analysis. Auto-generated tag-based LFs. Labeling function quality analysis. The label model outputs a large, probabilistic training data set that the platform can use to train a full ML model, which generalizes beyond the label model. Selecting tags in Snorkel Flow.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

phData

DECEMBER 29, 2022

This automation includes things like SQL translation during a data platform migration (SQLMorph), making changes to your Snowflake information architecture (Tram), and checking for parity and data quality between platforms (Data Source Automation). Let’s dive in and take a deeper look at these.

SQL 52

SQL Database Database Administration Data Profiling 52

phData

OCTOBER 17, 2024

dbt offers a SQL-first transformation workflow that lets teams build data transformation pipelines while following software engineering best practices like CI/CD, modularity, and documentation. The Data Source Tool can automate scanning DDL and profiling tables between source and target, comparing them, and then reporting findings.

AI 52

AI AI SQL Data Quality 52

Iguazio

FEBRUARY 20, 2024

What are the Key Elements of Data Management in Gen AI? The data pipeline ingests data from different sources and performs multiple actions like transformations, cleaning, versioning, tagging, labeling, indexing and more. This is essential for ensuring high quality outputs, which lead to high quality models.

AI 52

AI AI Data Pipeline Data Quality 52

Alation

OCTOBER 5, 2021

It’s on Data Governance Leaders to identify the issues with the business process that causes users to act in these ways. Inconsistencies in expectations can create enormous negative issues regarding data quality and governance. Establish a data governance program that drives business value by aligning team roles to KPIs.

Data Governance 96

Data Governance Data Quality Data Silos Analytics 96

Smart Data Collective

OCTOBER 4, 2021

There is no question that big data is very important for many businesses. Unfortunately, big data is only as useful as it is accurate. Data quality issues can cause serious problems in your big data strategy. It relies on data to drive its AI algorithms. What social media influencers connect with customers?

Big Data 113

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Pickl AI

JUNE 23, 2023

This involves cleaning the data, removing noise and inconsistencies, handling missing values, and transforming it into a suitable format for AI algorithms. Data Annotation In many AI applications, data annotation is necessary to label or tag the data with relevant information.

AI 52

AI AI Data Governance Data Quality 52

Dataconomy

JANUARY 23, 2024

Although they promise efficiency and automation, high-end tools frequently have premium price tags, and the initial outlay can be intimidating. It is critical to weigh the financial implications of incorporating AI into your web design process. You might need to invest in training to fully utilize these tools.

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Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. It isn't easy to collect a good amount of quality data. You need to know two basic terminologies here, Features and Labels.

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Machine Learning Machine Learning ML ML 109

Precisely

JULY 18, 2024

Unlike traditional metadata, which typically describes static attributes and properties of data (such as data type, size, and creation date), active metadata goes further by actively participating in and influencing the behavior of data management processes and workflows – providing real-time insights and influencing operational decisions.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

phData

OCTOBER 12, 2022

Exposures and Their Quality On the note of documentation, dbt provides a piece of documentation known as exposure. It allows you to tag which final models are being used for a particular data product or dashboard.

SQL 52

SQL Data Warehouse Data Visualization Data Quality 52

AssemblyAI

OCTOBER 31, 2024

Innovation #3: neural text formatting pipeline Perhaps the most visible improvement in Universal-2 is its ability to produce properly formatted output. It's why 73% of users preferred Universal-2 in blind tests over Universal-1.

AI 59

AI AI Data Quality Analytics 59

ODSC - Open Data Science

JUNE 19, 2023

These technologies include the following: Data governance and management  — It is crucial to have a solid data management system and governance practices to ensure data accuracy, consistency, and security. It is also important to establish data quality standards and strict access controls.

Big Data 96

Big Data Big Data Artificial Intelligence Artificial Intelligence 96

Alation

FEBRUARY 13, 2020

They may reside in a data lake, warehouse, master data repository, or any other shared data resource. People metadata describes those who work with data—consumers, curators, stewards, subject matter experts, etc. Search metadata supports tagging and keywords to help people find data.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

Snorkel AI

SEPTEMBER 29, 2023

At a basic level, data labeling prepares data sets to teach models what inputs correspond to which outputs. This process takes raw documents, files, or tabular records and adds one or more tags or labels to each. This approach applies across all data modalities. Poor data quality. Privacy concerns.

Machine Learning 59

Machine Learning Machine Learning Data Science ML 59

Women in Big Data

DECEMBER 13, 2023

Sonal talked about applications of LLMs as in – Content generation, Part-of-speech (POS) tagging, Question answering, Text summarization, Sentiment analysis, Conversational AI, Machine translation and Code completion. Image Credit: Neebal Technologies LLMs are not free from challenges. With issues also come the challenges.

Natural Language Processing 52

Natural Language Processing Big Data Big Data Computer Science 52

Alation

JUNE 30, 2021

The Alation platform includes ‘Allie,’ Alation’s AI, which helps determine what incomplete tags or column names mean (in a department-specific context) and smooths out inconsistent terminology,” the report details. The Data Catalog Solution. Intelligent SQL Editor. See the report for full details.

SQL 52

SQL ML ML Data Governance 52

Google Research AI blog

MARCH 27, 2023

The explicit tagging of various phenomena in PRESTO allows us to create different test sets to separately analyze model performance on these speech phenomena. We find that some of these phenomena are easier to model with few-shot examples, while others require much more training data.

Natural Language Processing 98

Natural Language Processing Data Quality 98

IBM Data Science in Practice

MARCH 8, 2023

Source: IBM Cloud Pak for Data Feature Catalog Users can manage feature definitions and enrich them with metadata, such as tags, transformation logic, or value descriptions. Source: IBM Cloud Pak for Data MLOps teams often struggle when it comes to integrating into CI/CD pipelines.

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Machine Learning Machine Learning ML ML 264

Pickl AI

AUGUST 21, 2024

Data Collection : The crawler collects information from each page it visits, including the page title, meta tags, headers, and other relevant data. This efficiency saves time and resources in data collection efforts. then follows these links to continue the crawling process, creating a web of interconnected pages.

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Apache Hadoop Hadoop Database Data Quality 52

The MLOps Blog

MARCH 15, 2023

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Snorkel AI

MARCH 14, 2023

Labeling unstructured data for ML projects has traditionally involved humans tagging each data point manually. Users are able to rapidly improve training data quality and model performance using integrated error analysis and model-guided feedback to develop highly accurate and adaptable AI applications.

AI 52

AI AI Data Scientist ML 52

Snorkel AI

MARCH 14, 2023

Labeling unstructured data for ML projects has traditionally involved humans tagging each data point manually. Users are able to rapidly improve training data quality and model performance using integrated error analysis and model-guided feedback to develop highly accurate and adaptable AI applications.

AI 52

AI AI Data Scientist ML 52

Pickl AI

AUGUST 27, 2024

Mobile Data Collection Tools These tools leverage smartphones and tablets to gather data on the go, often used in remote areas or fieldwork. KoboToolbox: Designed for humanitarian work, useful for field data collection with features like GPS tagging and photo capture.

Data Analysis 52

Data Analysis Data Analysis Database Power BI 52

IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

Alation

JUNE 14, 2021

According to a 2020 451 Research report , “data catalogs are rapidly building out automated functionality,” including “automated suggestions, automated discovery and tagging, and automated data-quality scoring.” These are essential to enabling a more rapid process of sensitive data discovery.

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97

AWS Machine Learning Blog

AUGUST 4, 2023

Create your secret with the following key-value pairs: { "identity_provider": "SALESFORCE", "authorization_url": "[link] "token_url": "[link] "client_id": " ", "client_secret": " " “issue_url”: “ ” } Add a tag with the key sagemaker:partner and your choice of value. In the data flow view, you can now see a new node added to the visual graph.

ML 84

ML ML AWS AI 84

The MLOps Blog

JANUARY 25, 2023

This data is then used to train models and make inferences. Since the data is prepared by humans, the data is likely prone to human biases. For example, “I love being ignored” may be tagged as a negative example, and “I can be very ambitious” can be tagged as a positive example.

Natural Language Processing 52

Natural Language Processing ML ML Deep Learning 52

IBM Journey to AI blog

JULY 3, 2024

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

AI 45

AI AI Data Quality Database 45

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

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Flipboard

MARCH 22, 2023

We also detail the steps that data scientists can take to configure the data flow, analyze the data quality, and add data transformations. Finally, we show how to export the data flow and train a model using SageMaker Autopilot. In the Tags section, add a tag with the key SageMaker and value true.

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