Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. Data pipeline orchestration.

Data Governance 59

Data Governance ML ML Cloud Data 59

Tableau

OCTOBER 8, 2021

Connecting directly to this semantic layer will help give customers access to critical business data in a safe, governed manner. This partnership makes data more accessible and trusted. Our continued investments in connectivity with Google technologies help ensure your data is secure, governed, and scalable.

Tableau 138

Tableau Analytics Analytics Machine Learning 138

DagsHub

APRIL 7, 2024

Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines. These pipelines cover the entire lifecycle of an ML project, from data ingestion and preprocessing, to model training, evaluation, and deployment.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

phData

AUGUST 5, 2024

Who should have access to sensitive data? How can my analysts discover where data is located? All of these questions describe a concept known as data governance. The Snowflake AI Data Cloud has built an entire blanket of features called Horizon, which tackles all of these questions and more.

Data Governance 52

Data Governance Data Quality Data Lakes ML 52

Alation

JUNE 21, 2022

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. ML and DataOps teams). data pipelines) to support.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Pickl AI

OCTOBER 17, 2024

Automation Automation plays a pivotal role in streamlining ETL processes, reducing the need for manual intervention, and ensuring consistent data availability. By automating key tasks, organisations can enhance efficiency and accuracy, ultimately improving the quality of their data pipelines.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Tableau

OCTOBER 8, 2021

Connecting directly to this semantic layer will help give customers access to critical business data in a safe, governed manner. This partnership makes data more accessible and trusted. Our continued investments in connectivity with Google technologies help ensure your data is secure, governed, and scalable. .

Tableau 98

Tableau Analytics Analytics Machine Learning 98

phData

FEBRUARY 14, 2023

To address these issues, they need a centralized and integrated data platform that serves as a single source of truth, preferably with strong data governance capabilities. As the insurance industry continues to generate a wider range and volume of data, it becomes more challenging to manage data classification.

Data Governance 52

Data Governance Data Silos Predictive Analytics Data Wrangling 52

DagsHub

AUGUST 23, 2024

As companies increasingly rely on data for decision-making, poor-quality data can lead to disastrous outcomes. Even the most sophisticated ML models, neural networks, or large language models require high-quality data to learn meaningful patterns. When bad data is inputted, it inevitably leads to poor outcomes.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Iguazio

FEBRUARY 20, 2024

Building MLOpsPedia This demo on Github shows how to fine tune an LLM domain expert and build an ML application Read More Building Gen AI for Production The ability to successfully scale and drive adoption of a generative AI application requires a comprehensive enterprise approach. Let’s dive into the data management pipeline.

AI 52

AI AI Data Pipeline Analytics 52

IBM Journey to AI blog

DECEMBER 16, 2022

And because data assets within the catalog have quality scores and social recommendations, Alex has greater trust and confidence in the data she’s using for her decision-making recommendations. This is especially helpful when handling massive amounts of big data. Protected and compliant data.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Alation

APRIL 14, 2023

Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys.

Data Pipeline 52

Data Pipeline Data Warehouse Cloud Data ETL 52

The MLOps Blog

MARCH 15, 2023

This includes the tools and techniques we used to streamline the ML model development and deployment processes, as well as the measures taken to monitor and maintain models in a production environment. Costs: Oftentimes, cost is the most important aspect of any ML model deployment. This includes data quality, privacy, and compliance.

AWS 52

AWS ETL ML ML 52

Snorkel AI

MAY 12, 2023

Piyush Puri: Please join me in welcoming to the stage our next speakers who are here to talk about data-centric AI at Capital One, the amazing team who may or may not have coined the term, “what’s in your wallet.” What can get less attention is the foundational element of what makes AI and ML shine. That’s data.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

Piyush Puri: Please join me in welcoming to the stage our next speakers who are here to talk about data-centric AI at Capital One, the amazing team who may or may not have coined the term, “what’s in your wallet.” What can get less attention is the foundational element of what makes AI and ML shine. That’s data.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

phData

APRIL 18, 2023

Snowflake enables organizations to instantaneously scale to meet SLAs with timely delivery of regulatory obligations like SEC Filings, MiFID II, Dodd-Frank, FRTB, or Basel III—all with a single copy of data enabled by data sharing capabilities across various internal departments.

Data Silos 52

Data Silos ETL Clustering Analytics 52

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Machine Learning Integration Opportunities Organizations harness machine learning (ML) algorithms to make forecasts on the data.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. It’s not just a dumping ground for data, but a crucial step in your customer data processing workflow.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

Precisely

SEPTEMBER 30, 2024

Data enrichment adds context to existing information, enabling business leaders to draw valuable new insights that would otherwise not have been possible. Managing an increasingly complex array of data sources requires a disciplined approach to integration, API management, and data security.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

phData

JULY 18, 2023

Why Migrate to a Modern Data Stack? Data teams can focus on delivering higher-value data tasks with better organizational visibility. Move Beyond One-off Analytics: The Modern Data Stack empowers you to elevate your data for advanced analytics and integration of AI/ML, enabling faster generation of actionable business insights.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

phData

MAY 28, 2024

Cortex ML functions are aimed at Predictive AI use cases, such as anomaly detection, forecasting , customer segmentation , and predictive analytics. The combination of these capabilities allows organizations to quickly implement advanced analytics without the need for extensive data science expertise.

Machine Learning 52

Machine Learning Machine Learning Data Engineering Data Engineering 52

Alation

APRIL 19, 2022

Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. Access the resources your data applications need — no more, no less. Data Pipeline Automation. What Is the Role of Data Governance in Data Modernization?

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

IBM Journey to AI blog

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Lakes 73

Data Lakes AI AI Data Governance 73

AWS Machine Learning Blog

NOVEMBER 12, 2024

There are various technologies that help operationalize and optimize the process of field trials, including data management and analytics, IoT, remote sensing, robotics, machine learning (ML), and now generative AI. The first step in developing and deploying generative AI use cases is having a well-defined data strategy.

AWS 113

AWS AI AI Data Lakes 113

AWS Machine Learning Blog

DECEMBER 18, 2024

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. She specializes in AI operations, data governance, and cloud architecture on AWS.

Clustering 98

Clustering AWS AI AI 98