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 333

Management Machine Learning Experimentation Metrics 333

Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. Moving to the “optimal” stage of maturity is critical to eliminating unauthorized access by bad actors, both foreign and domestic.

Metadata 83

Metadata Data Lake Optimization Modeling 83

Smart Data Collective

MAY 11, 2023

App analytics provide valuable insights that help identify bottlenecks, improve user experience, and optimize marketing campaigns. AI analytics is a part of business intelligence that uses machine learning to find patterns and relationships in data.

Cost-Benefit 97

Cost-Benefit Optimization Data-driven Marketing 97

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 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

CIO Business Intelligence

OCTOBER 13, 2023

Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

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

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 96

Management Big Data Metadata Data Warehouse 96

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

AWS Big Data

MAY 31, 2024

This encompasses tasks such as integrating diverse data from various sources with distinct formats and structures, optimizing the user experience for performance and security, providing multilingual support, and optimizing for cost, operations, and reliability. Based on metadata, content is returned from Amazon S3 to the user.

Metadata 107

Metadata Management Testing Data-driven 107

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

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

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.

Metadata 78

Metadata Data Warehouse Forecasting Predictive Modeling 78

CIO Business Intelligence

MARCH 24, 2023

Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. IBM Data Governance IBM Data Governance leverages machine learning to collect and curate data assets. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

FEBRUARY 14, 2024

Introduce gen AI capabilities without thinking about data hygiene, he warns, and people will be disillusioned when they haven’t done the pre work to get it to perform optimally. At the beginning of 2023, Gartner reported only 15% of organizations already have data storage management solutions that classify and optimize data.

IT 143

IT Metadata Data-driven Management 143

CIO Business Intelligence

DECEMBER 13, 2023

and applying and enriching metadata helps organizations take a big step toward innovating with generative AI. Digitizing relevant physical assets and objects, such as those core samples, IT equipment, office equipment, etc.

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

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

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 88

Metrics Data Governance Cost-Benefit Dashboards 88

CIO Business Intelligence

NOVEMBER 22, 2022

The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

DECEMBER 4, 2023

As data skyrockets—especially unstructured data—organizations need an intentional plan and ongoing approach to protect, manage, and optimize data for monetization. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

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 70

Digital Transformation Machine Learning Optimization Data Lake 70

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

CIO Business Intelligence

SEPTEMBER 18, 2023

The speed at which these networks are operating, and the immense data flows transiting the network, necessitate dynamic tools to automate and streamline migration and optimize day-to-day operations,” says Leigh, research manager of mobility and 5G at IDC. “A

Data mining 111

Data mining Testing Metadata Enterprise 111

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

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

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

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

JULY 14, 2023

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. Hive creates Iceberg’s metadata files for the same exact table.

Snapshot 70

Snapshot Metadata Data Warehouse Testing 70

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

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data.

Data Lake 113

Data Lake Analytics Dashboards Metrics 113

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. The shift away from ‘Software 1.0’ where applications have been based on hard-coded rules has begun and the ‘Software 2.0’

Data Governance 145

Data Governance IT Risk Data Lake 145

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. Cloudera customers run some of the biggest data lakes on earth. The second generation of the Hive Metastore added support for transactional updates with Hive ACID.

Data Lake 94

Data Lake Data Warehouse Machine Learning Cost-Benefit 94

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Cloudera customers run some of the biggest data lakes on earth. The second generation of the Hive Metastore added support for transactional updates with Hive ACID.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

SEPTEMBER 29, 2020

Running on highly optimized Kubernetes engines, CDW can quickly and automatically scale up and down based on actual query workload, providing optimum utilization of cloud (public as well as private) resources and budget. The post Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark appeared first on Cloudera Blog.

Data Warehouse 120

Data Warehouse Metadata Data-driven Machine Learning 120

Cloudera

DECEMBER 11, 2020

Running on highly optimized Kubernetes engines, CDW can quickly and automatically scale up and down based on actual query workload, thereby providing optimum utilization of cloud (public as well as private) resources and budget. Learn more about Cloudera Data Warehouse on CDP.

Data Warehouse 110

Data Warehouse Metadata Machine Learning Measurement 110

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. It doesn’t conform to a data model but does have associated metadata that can be used to group it.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Structured Data 137

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