erwin

JANUARY 7, 2021

AI-Fueled Data Governance: Artificial intelligence (AI) has been narrowly tied to the internet of things (IoT) with smart features like Alexa, Nest and self-driving cars. This year, that will change as semantic metadata comes into its own driven by Microsoft’s Common Data Model (CDM). Click here to learn more and register.

Metadata 98

Metadata Data Governance Internet of Things IoT 98

AWS Big Data

MARCH 13, 2024

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS. Choose Run.

Analytics 94

Analytics IoT Metadata Internet of Things 94

CIO Business Intelligence

FEBRUARY 14, 2024

That’s not just about the cost of preparing a larger data set than you need, which takes expertise that’s still uncommon and commands a high salary, but also what you’re teaching the model. Do you want to have an even more powerful search capability with AI in your data, and to be unsure about how you’ve organized that data?”

IT 140

IT Metadata Data-driven Management 140

Cloudera

AUGUST 3, 2021

Risk modeling was once a qualitative guess, now modeling can leverage enterprise data to deliver quantitative assessments from a larger and more diverse data set. The classical approach to just-in-time delivery, delivering raw material or product at the moment of need with zero inventory, is outdated.

Analytics 111

Analytics Digital Transformation Forecasting Risk 111

Cloudera

SEPTEMBER 23, 2020

Access audits are mastered centrally in Apache Ranger which provides comprehensive non-repudiable audit log for every access event to every resource with rich access event metadata such as: IP. Both fine-grained access control of database objects and access to metadata is provided. User, business classification of asset accessed.

Data Lake 84

Data Lake Metadata IoT Enterprise 84

IBM Big Data Hub

JUNE 30, 2022

With technologies like machine learning , artificial intelligence or IoT, the resulting insights are more sophisticated and valuable, especially when woven into your organization’s processes and workflows. Think big, but prioritize and articulate realistic and actionable plans, establishing the right partnership models along the way.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. HYBRID & MULTI-CLOUD INNOVATION.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

AWS Big Data

MAY 4, 2023

After deployment, the user will have access to a Jupyter notebook, where they can interact with two datasets from ASDI on AWS: Coupled Model Intercomparison Project 6 (CMIP6) and ECMWF ERA5 Reanalysis. The OpenSearch Service domain stores metadata on the datasets connected at the Regions.

Data Processing 94

Data Processing Metadata Informatics Interactive 94

Jet Global

JUNE 5, 2019

Essentially, data mining is the process of extracting data from different sources (such as retail point of sale software, logistics management tools, and IoT-equipped manufacturing machinery), analyzing it, and summarizing it with reports or dashboards that can help businesses gain insight into their operations.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Jet Global

JULY 2, 2019

This is particularly useful when capturing event tracking or IoT data; though the uses of data lakes extend beyond just those scenarios. At the very worst, data lakes can provide a wealth of data that is impossible to analyze in a meaningful way due to incorrect metadata or cataloging. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Cloudera

AUGUST 30, 2018

Digital technologies are changing business models, reshaping how companies go-to-market, win new customers and drive new revenue-producing opportunities. Complicating matters is the increasing focus on data protection and the far-reaching implications of IoT (e.g. connected cars, cities, wearables, phones, etc.).

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

AWS Big Data

FEBRUARY 20, 2024

You can ingest and integrate data from multiple Internet of Things (IoT) sensors to get insights. However, you may have to integrate data from multiple IoT sensor devices to derive analytics like equipment health information from all the sensors based on common data elements.

IoT 94

IoT Analytics Prescriptive Analytics Internet of Things 94

In(tegrate) the Clouds

DECEMBER 21, 2015

At the same time, big data solutions will mature (read: security, governance, metadata management) and go beyond the role of being primarily developer tools for highly skilled programmers. It’s software plus business model disruption and the right mix of timing that will lead to massive customer attraction in 2016.

Technology 45

Technology Internet of Things Digital Transformation Software 45

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. Cloud governance.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Ontotext

FEBRUARY 3, 2022

Thanks to internet-of-things (IoT) enabled machinery, the globalization of supply lines, and the proliferation of technical standards, 21st century manufacturing requires 21st century techniques. Running an analysis of this digital model allows companies to identify what could go wrong and proactively intervene. See figure 1.).

Manufacturing 52

Manufacturing IoT Internet of Things Interactive 52

erwin

FEBRUARY 4, 2021

Sources, like IoT. This is an aspect of data lineage, created from technical metadata, ensuring nothing “breaks” along the change train. Points of integration. Regulations. Impact analysis has equal importance to IT for automatically tracking changes and understanding how data from one system feeds other systems and reports.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

IBM Big Data Hub

JANUARY 18, 2023

Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. For these workloads, data lake vendors usually recommend extracting data into flat files to be used solely for model training and testing purposes.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

Cloudera

NOVEMBER 13, 2020

Data science experiment result and performance analysis, for example, calculating model lift. Operational, Cybersecurity, and IoT reporting where the current point in time state of an individual or single device needs to be analyzed. . Metadata Caching. This includes the time to fetch the metadata and schema for our tables.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

IBM Big Data Hub

AUGUST 7, 2023

Orion combines these capabilities with other blockchain properties, offering tamper evidence, provenance, data lineage, authenticity and non-repudiation, all while utilizing a standard data model and transactional APIs. Orion’s technology is highly valuable in enhancing system integrity and reducing errors, disputes and fraud.

Data Governance 63

Data Governance Manufacturing Interactive IoT 63

Cloudera

JUNE 25, 2019

Overwhelmed by new data – images, video, sensor and IoT. Secure and governed – simplifies data privacy and compliance for diverse enterprise data with a common security model to control data on any cloud – public, private and hybrid. Struggling to combat proliferating silos and control their customers’ and operations data.

Enterprise 87

Enterprise Machine Learning Recreation/Entertainment IoT 87

Cloudera

JANUARY 22, 2019

The top Big Data Fabric use cases recognized by Forrester are 360-degree view of the customer, Internet-of-things (IoT) analytics, and real-time and advanced analytics. Cloudera Enterprise Platform as Big Data Fabric. An organization needs a unified data management and analytics platform that can support its business objectives.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

erwin

JANUARY 3, 2020

While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping into the true value of data as the foundation of the digital business model. Data Modeling: Drive Business Value and Underpin Governance with an Enterprise Data Model.

Data Governance 139

Data Governance Digital Transformation IoT Metadata 139

Cloudera

OCTOBER 7, 2021

difficulty to achieve cross-organizational governance model). Data and Metadata: Data inputs and data outputs produced based on the application logic. Data Cataloging: SDX offers a sophisticated data cataloging capability that enables capturing both business and technical metadata of Data Products.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

Cloudera

JULY 20, 2021

Once companies are able to leverage their data they’re then able to fuel machine learning and analytics models, transforming their business by embedding AI into every aspect of their business. . Risk models for financial institutions and insurers are exponentially more complicated . Airline schedules and pricing algorithms.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

erwin

JANUARY 3, 2020

While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping into the true value of data as the foundation of the digital business model. Data Modeling: Drive Business Value and Underpin Governance with an Enterprise Data Model.

Data Governance 52

Data Governance Digital Transformation IoT Metadata 52

Cloudera

MAY 22, 2019

Although the program is technically in its seventh year, as the first joint awards program, this year’s Data Impact Awards will span even more use cases, covering even more advances in IoT, data warehouse, machine learning, and more. If you’ve democratized data within your company, we want to hear from you. DATA SECURITY AND GOVERNANCE.

Machine Learning 56

Machine Learning Data Architecture IoT Metadata 56

Cloudera

MAY 18, 2021

Prior the introduction of CDP Public Cloud, many organizations that wanted to leverage CDH, HDP or any other on-prem Hadoop runtime in the public cloud had to deploy the platform in a lift-and-shift fashion, commonly known as “Hadoop-on-IaaS” or simply the IaaS model. data streaming, data engineering, data warehousing etc.),

Cost-Benefit 86

Cost-Benefit Data-driven Data Warehouse Machine Learning 86