Octopai

SEPTEMBER 14, 2020

Modern data processing depends on metadata management to power enhanced business intelligence. Metadata is of course the information about the data, and the process of managing it is mysterious to those not trained in advanced BI. In this article, you will learn: What does metadata management do? Automated Data Discovery.

Metadata 52

Metadata Management Data Processing Machine Learning 52

AWS Big Data

FEBRUARY 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. MongoDB Atlas is a developer data service from AWS technology partner MongoDB, Inc.

Metadata 77

Metadata Data Lake Machine Learning Management 77

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. Forbes Technology Council.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. Another perspective on technology-induced business disruption (including ChatGPT deployments) is to consider the three F’s that affect (and can potentially derail) such projects.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

AWS Big Data

OCTOBER 25, 2023

However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. But in the case of unstructured data, metadata discovery is challenging because the raw data isn’t easily readable. You can integrate different technologies or tools to build a solution.

Unstructured Data 121

Unstructured Data Metadata Management Analytics 121

Analytics Vidhya

SEPTEMBER 17, 2022

Any type of contextual information, like device context, conversational context, and metadata, […]. However, we can improve the system’s accuracy by leveraging contextual information. The post Underlying Engineering Behind Alexa’s Contextual ASR appeared first on Analytics Vidhya.

Metadata 368

Metadata Statistics Data Science Publishing 368

DataRobot Blog

MARCH 16, 2023

This integration takes the power of one of the most advanced large language model technologies that exists today in Azure OpenAI Service, and through DataRobot, drives value-centric outcomes with machine learning. This saves us the time it would otherwise take to memorize metadata and APIs.

Data Science 98

Data Science Technology Data-driven Modeling 98

AWS Big Data

APRIL 19, 2023

This post shows how to use machine learning (ML) and Amazon Neptune to create automated recommendations to join data products and display those recommendations alongside the existing data products. To learn more about ML in Neptune, refer to Amazon Neptune ML for machine learning on graphs.

Technology 85

Technology Data-driven Machine Learning Sales 85

Ontotext

JANUARY 10, 2024

The larger an organisation, the more complex it will naturally be, needing more people and technologies to serve a growing customer base – PwC, Is your organisation too complex to secure? Any type of metadata or universal data model is likely to slow down development and increase costs, which will affect the time to market and profit.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

O'Reilly on Data

JANUARY 29, 2019

In 2018, we decided to run a follow-up survey to determine whether companies’ machine learning (ML) and AI initiatives are sustainable—the results of which are in our recently published report, “ Evolving Data Infrastructure.”. Here are some notable findings from the survey: Companies are serious about machine learning and AI.

Deep Learning 207

Deep Learning Machine Learning Data Science Metadata 207

Octopai

NOVEMBER 5, 2019

A data dictionary is a technical representation of the metadata associated with a data object, such as a database, table, or column. A data dictionary serves as the technical basis of a comprehensive data governance program, because data governance relies on the underlying metadata. Data Dictionaries. What is a data dictionary ?

Machine Learning 44

Machine Learning Metadata Data Governance Data Warehouse 44

O'Reilly on Data

JANUARY 8, 2019

In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. We are also seeing more training programs aimed at executives and decision makers , who need to understand how these new ML technologies can impact their current operations and products.

IoT 201

IoT Machine Learning Internet of Things Data Science 201

O'Reilly on Data

FEBRUARY 11, 2020

Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. Just 20% of organizations publish data provenance and data lineage.

Data Quality 299

Data Quality Metadata Data Governance Publishing 299

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 327

Management Machine Learning Experimentation Metrics 327

AWS Big Data

JANUARY 16, 2024

Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. Within Airflow, the metadata database is a core component storing configuration variables, roles, permissions, and DAG run histories. A healthy metadata database is therefore critical for your Airflow environment.

Strategy 102

Strategy Metadata Metrics Dashboards 102

Smart Data Collective

APRIL 5, 2022

They are using tools like Amazon SageMaker to take advantage of more powerful machine learning capabilities. Amazon SageMaker is a hardware accelerator platform that uses cloud-based machine learning technology. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

Ontotext

DECEMBER 1, 2023

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. It was presented by Summit Pal, Strategic Technology Director at Ontotext and former Gartner VP Analyst.

Metadata 78

Metadata Sales Consulting Enterprise 78

Ontotext

SEPTEMBER 7, 2023

Graph technologies are a way to store and represent data in a more graphical way. When I try to explain what I do I’d say, “Have you used Google, or DBpedia, or Uber, or any of these things that have graph technology embedded?” People are beginning to realize what graph technology is. This is just my perception.

Technology 59

Technology Visualization Digital Transformation Management 59

IBM Big Data Hub

FEBRUARY 22, 2024

Defense leaders focused on operationalizing the responsible curation of AI must first agree upon a shared vocabulary—a common culture that guides safe, responsible use of AI—before they implement technological solutions and guardrails that mitigate risk. But AI also supports other strategic goals of the DoD.

Metadata 94

Metadata Measurement Risk Modeling 94

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. Today is a revolutionary moment for Artificial Intelligence (AI). AI is already driving results for business. Watsonx.ai

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. The data architect is responsible for visualizing and designing an organization’s enterprise data management framework.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

Ontotext

AUGUST 4, 2023

As data is generated, stored, and used across data centers, edge, and cloud providers, managing a distributed storage environment is complex with no map to guide technology professionals. Using metadata, machine learning (ML), and automation, a data fabric provides a unified view of enterprise data across data formats and locations.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Cloudera

DECEMBER 15, 2022

You can leverage Kubernetes (K8s) and containerization technologies to consistently deploy your applications across multiple clouds including AWS, Azure, and Google Cloud, with portability to write once, run anywhere, and move from cloud to cloud with ease. Only metadata will be regenerated. Metadata management .

Metadata 78

Metadata Data Warehouse Snapshot Data Quality 78

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Metadata and artifacts needed for a full audit trail.

Modeling 193

Modeling Machine Learning Testing Metrics 193

AWS Big Data

DECEMBER 13, 2023

EDLS job steps and metadata Every EDLS job comprises one or more job steps chained together and run in a predefined order orchestrated by the custom ETL framework. The metadata holds configurations for the file ingestion step to connect to Amazon S3 or SFTP endpoints and ingest files to target location.

Metadata 91

Metadata Data Lake Visualization Data Transformation 91

AWS Big Data

NOVEMBER 17, 2023

These include internet-scale web and mobile applications, low-latency metadata stores, high-traffic retail websites, Internet of Things (IoT) and time series data, online gaming, and more. Table metadata, such as column names and data types, is stored using the AWS Glue Data Catalog. You don’t need to write any code. Choose Next.

Visualization 85

Visualization Metadata Testing Internet of Things 85

BI-Survey

MARCH 23, 2023

It is mainly used for data cataloging, data governance, compliance & regulatory use cases or as a metadata hub. Metadata can be extracted from any source and made available. Automation to support metadata curation processes (e.g., by machine learning) is not available yet, but work is underway on this.

Metadata 52

Metadata Marketing Data Quality Machine Learning 52

Ontotext

APRIL 19, 2024

We mainly talked about the company’s Metadata Studio and the types of features it has that give users the options I’ve listed above. NLP and the role of metadata-oriented feedback loops Moreover, text analysis or mining can add to that meaning and contribute even more to the knowledge in the graph.

Metadata 52

Metadata Statistics Interactive Enterprise 52

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Smart Data Collective

MAY 11, 2023

Since the launch of Smart Data Collective, we have talked at length about the benefits of AI for mobile technology. Bhaval Patel of Space-O Technologies wrote a blog post about the growing importance of AI for mobile apps. AI-powered analytics technology has helped e-commerce companies leverage the benefits of analytics even more.

Cost-Benefit 97

Cost-Benefit Optimization Data-driven Marketing 97

CIO Business Intelligence

MARCH 7, 2024

They have a ton of data, due to their massive customer base, from which to train models, as well as the metadata, which is the data that describes or carries the attributes of that data, like flows, mappings, and business rules,” says Kirkpatrick, research director at Futurum. But he’s not ready to call a favorite.

Enterprise 109

Enterprise Metadata Data-driven Modeling 109

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

AWS Big Data

NOVEMBER 15, 2023

Additionally, it incorporates BMW Group’s internal system to integrate essential metadata, offering a comprehensive view of the data across various dimensions, such as group, department, product, and applications. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

CIO Business Intelligence

APRIL 30, 2024

Together the technologies aim to help business users and “novice” data analysts explore their data and gain insights without having to resort to data experts. The copilot would then use the data source’s metadata and field names to provide a detailed description of the data, enabling other analysts to more easily reference the insights.

Analytics 74

Analytics Metrics Visualization Dashboards 74

DataKitchen

AUGUST 8, 2023

Data Observability technology learns what to monitor and provides insights into unforeseen exceptions. She sees Data Observability as an emerging technology in data engineering and management. Traditional monitoring tools need to be more comprehensive to address new issues not previously understood or detected.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

Alation

MAY 31, 2023

Select and implement data tools and technologies. They curate metadata about assets and develop technical solutions. Managing metadata Managing metadata is essential for ensuring the accuracy and completeness of an organization’s data. Maintain data models and documentation. Ensure data security and compliance.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52