CIO Business Intelligence

DECEMBER 13, 2023

and applying and enriching metadata helps organizations take a big step toward innovating with generative AI. User-generated content , such as blogs, forums, and customer feedback, to understand customer preferences, improve product recommendations, and tailor user experiences.

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

Ontotext

APRIL 19, 2024

You can switch out or add to the assisted tagging capabilities you can work with based on the benchmarking, so you’re able to optimize the result. 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. Ivo’s been at Ontotext for over 14 years.

Metadata 52

Metadata Statistics Interactive Enterprise 52

Cloudera

AUGUST 3, 2021

Advanced predictive analytics and modeling are now optimizing safety stocks and supply chains to include the element in risk so that optimized inventory levels and redundant capital deployment in high risk manufacturing processes are optimized. Digital Transformation is not without Risk. Open source solutions reduce risk.

Analytics 111

Analytics Digital Transformation Forecasting Risk 111

Cloudera

JANUARY 5, 2023

Faced with even more pressure to remain resilient and agile amid looming global economic threats, Asia-Pacific (APAC) region businesses are looking to further mobilize emerging technologies such as artificial intelligence (AI) and machine learning that will optimize operational efficiencies and cost savings. .

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

IBM Big Data Hub

APRIL 28, 2022

By using metadata-enriched AI and a semantic knowledge graph for automated data enrichment, a data fabric continuously identifies and connects data from disparate data stores to discover relevant relationships between the available data points. Learn more about a data fabric architecture and how it can benefit your organization.

Metadata 78

Metadata Data Warehouse Forecasting Predictive Modeling 78

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

Cloudera

JULY 14, 2023

In this blog, I will describe a few strategies one could undertake for various use cases. They simply read the underlying data (not even full read, they just read the parquet headers) and create corresponding Iceberg metadata files. You could optimize your table now or at a later stage using the “rewrite_data_files” procedure.

Snapshot 73

Snapshot Metadata Data Warehouse Testing 73

Cloudera

MARCH 22, 2023

SDX continually captures and manages both the active and passive metadata for data assets and the processes that work on them. Data services and workloads cover ingesting data, enriching it, making it available for analysis in (operational) dashboards, or using it to build AI and machine learning models.

Metrics 91

Metrics Data Governance Cost-Benefit Dashboards 91

Cloudera

DECEMBER 11, 2020

In a previous blog post on CDW performance, we compared Azure HDInsight to CDW. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 More on this later in the blog.

Data Warehouse 111

Data Warehouse Metadata Machine Learning Measurement 111

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). Capture and document model metadata for report generation.

Risk 71

Risk Modeling Management Metadata 71

Ontotext

MAY 2, 2024

Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources. Providing a unified metadata model and a semantic layer is enhanced through discovery, auto-classification, tagging, inferencing, and so on. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

SEPTEMBER 29, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 The post Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark appeared first on Cloudera Blog.

Data Warehouse 122

Data Warehouse Metadata Data-driven Machine Learning 122

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: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning.

Digital Transformation 71

Digital Transformation Machine Learning Optimization Data Lake 71

IBM Big Data Hub

APRIL 10, 2023

The approach should be designed to provide enough metadata that key HR decision makers can identify which processes and decisions are informed by AI while maintaining anonymity and privacy in the data itself. A similar correlation holds true in leveraging data to drive leadership performance in the ESG areas.

Strategy 86

Strategy Data Architecture Cost-Benefit Reporting 86

Ontotext

FEBRUARY 1, 2024

When our auto-categorization engine, Graphite Knowledge Studio, tags content with metadata derived from taxonomies, we also capture and store this content metadata inside the knowledge graph, thereby linking concepts to the content they describe. Synaptica engineers responded to this need with optimized search indexes and queries.

Enterprise 59

Enterprise Management Metadata Modeling 59

IBM Big Data Hub

SEPTEMBER 20, 2022

Organizations are increasingly depending upon artificial intelligence (AI) and Machine Learning (ML) to assist humans in decision making. Consider these three crucial steps in the lifecycle of building out your next AI or machine learning model or improving a current one. Comprehensive, trusted data sets.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. Meanwhile, the company’s IT teams could optimize their time by focusing on other important workloads. She can search structured or unstructured data, visualizations and dashboards, machine learning models, and database connections.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

JANUARY 15, 2021

Some examples of recent optimizations in Impala include: New multithreading model (see dedicated blog post ). Remote read optimizations: IMPALA-8341: Data cache for remote reads. Impala use of KRPC (see dedicated blog post ). Parquet page indexes (see dedicated blog post ). Benchmark Description.

Data Warehouse 99

Data Warehouse Cost-Benefit Consulting Interactive 99

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. If you want to learn more, join us on June 21 on our webinar with Ryan Blue, co-creator of Apache Iceberg and Anjali Norwood, Big Data Compute Lead at Netflix.

Data Lake 96

Data Lake Data Warehouse Machine Learning Cost-Benefit 96

Cloudera

DECEMBER 10, 2020

Cloud-native warehouses that fail economically usually don’t do a good job optimizing cloud resources as part of their core functionality. Therefore, optimizing the performance of the cloud-native data warehouse saves time and money. CDW optimizes storage. These techniques directly reduce costs. . Security is centralized.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. Customer-facing AI use cases Deliver superior customer service Customers can now be assisted in real time with conversational AI.

Cost-Benefit 83

Cost-Benefit Insurance Unstructured Data Machine Learning 83

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . Given this context, how can financial institutions reap the benefits of modern machine learning approaches, while still being compliant to their MRM framework?

Risk 64

Risk Modeling Machine Learning Data Quality 64

Ontotext

APRIL 15, 2020

In his blog post “ How knowledge graph technology is helping Cochrane respond to COVID-19 ” Paul Wilton presents in great detail the data modelling principle and the software architecture behind the register. Here, GraphDB is used for storing the ontology models, the vocabulary, the content metadata and the graphs from the PICO ontology.

Publishing 105

Publishing Metadata Data mining Technology 105

Alation

SEPTEMBER 16, 2021

AI & machine learning to learn from & scale brilliance. AI and machine learning play key roles on both sides, both learning from human behavior and automating the most repetitive tasks. Data intelligence complements human labor with machine learning. Metadata Management.

Machine Learning 52

Machine Learning Data Governance Software Metadata 52

Cloudera

FEBRUARY 11, 2019

In this blog, we share our takeaways as they relate to the DMSA market trends. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads. To learn more about Data Management Solutions for Analytics, Gartner subscribers can download Gartner’s report here.

Management 43

Management Metadata Analytics Machine Learning 43

CDW Research Hub

JULY 22, 2020

Furthermore, the need for real-time data processing as well as the rise of AI and machine learning applications demand fast and efficient storage solutions. It also ensures that the architecture maintains a low metadata footprint, with no assumption that all metadata always resides in the memory.

IT 52

IT Metadata Business Objectives Machine Learning 52

AWS Big Data

JUNE 7, 2023

This is a guest blog post co-written with Sumesh M R from Cargotec and Tero Karttunen from Knowit Finland. Through their unique position in ports, at sea, and on roads, they optimize global cargo flows and create sustainable customer value. An AWS Glue job (metadata exporter) runs daily on the source account.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

Cloudera

AUGUST 30, 2018

Machine learning driven business – A focus on the design of systems that can learn from and make decisions and predictions based on data. How can I optimize my rate of return and continue to drive innovation? The rest of this blog is focused on how Cloudera Enterprise 6.0 appeared first on Cloudera Blog.

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 85

Data Warehouse Cost-Benefit Metadata Data-driven 85

Ontotext

NOVEMBER 22, 2020

Businesses wanted a way to make pie and not an in-depth understanding of forward-chaining, inferential explosion or SPARQL optimizations. Content Enrichment and Metadata Management. The value of metadata for content providers is well-established.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

Cloudera

SEPTEMBER 28, 2020

Data Science and machine learning workloads using CDSW. Queue priorities needed to be reconfigured for optimal performance. Transition from Navigator by migrating the business metadata (tags, entity names, custom properties, descriptions and technical metadata (Hive, Spark, HDFS, Impala) to Atlas. on roadmap).

Testing 132

Testing Metadata Risk Data Science 132

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Sisense

MAY 28, 2020

Customers want to know that our platform will work seamlessly with their chosen cloud vendor, even if that just means something as basic-sounding as making sure queries between the vendor and Sisense are optimized.” That’s without mentioning outdated metadata—the data about data that provides data intelligence,” said Gopal.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Alation

OCTOBER 5, 2021

For organizations to succeed in monitoring, managing, and optimizing their data resources, they must always keep the importance of their data-driven initiatives at the top of all strategic planning agendas. For more information on developing an optimized data governance strategy, contact Alation today. [1] Subscribe to Alation's Blog.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Domino Data Lab

JULY 22, 2019

This blog post provides a concise session summary, a video, and a written transcript. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. Do they have a system to manage the metadata for given assets? Subscribe to Alation's Blog Get the latest data cataloging news and trends in your inbox.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Ontotext

FEBRUARY 16, 2023

This data can then be easily analyzed to provide insights or used to train machine learning models. Ontotext’s approach is to optimize models and algorithms through human contribution and benchmarking in order to create better and more accurate AI. You can read more about it in this blog post. What Is A Human Benchmark?

Metadata 59

Metadata Measurement Metrics Modeling 59