CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

NOVEMBER 28, 2023

We think that by automating the undifferentiated parts, we can help our customers increase the pace of their data-driven innovation by breaking down data silos and simplifying data integration.

Data Warehouse 99

Data Warehouse Data-driven Machine Learning B2B 99

CIO Business Intelligence

APRIL 25, 2022

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. They require specific data inputs, models, algorithms and they deliver very specific recommendations.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

SEPTEMBER 20, 2023

With this functionality, you’re empowered to focus on extracting valuable insights from their data, while AWS Glue handles the infrastructure heavy lifting using a serverless compute model. She is a data enthusiast who enjoys problem solving and tackling complex architectural challenges with customers. Big Data Architect.

Interactive 97

Interactive Visualization Measurement Data Architecture 97

Ontotext

JULY 9, 2020

There is no easy answer to these questions but we still need to make sense of the data around us and figure out ways to manage and transfer knowledge with the finest granularity of detail. Knowledge graphs, the ones with semantically modeled data even more so , allow for such a granularity of detail.

Data Architecture 128

Data Architecture Unstructured Data Enterprise Technology 128

CIO Business Intelligence

MAY 2, 2022

Ken Finnerty, vice president of information technology at overall winner UPS , will discuss how the shipping giant thinks about innovation and tools like artificial intelligence and data architecture with Chandana Gopal, IDC’s research director for Future of Intelligence. Check out the full summit agenda here.

Advertising 98

Advertising Data Governance Insurance Strategy 98

Ontotext

APRIL 10, 2024

Knowledge graphs and semantic metadata Knowledge graphs (KGs) are the key to: Advanced Data Architecture & Models like Data Fabric, Data Mesh Unified Data Access Semantic Data Integration These fundamental capabilities of KGs enable them to bridge the chasm between information and knowledge in the DIKW pyramid.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 67

Data Quality Data Integration Metadata Cost-Benefit 67

TDAN

AUGUST 18, 2020

Flexibility is one strong driver: heterogeneous data, integrating new data sources, and analytics all require flexibility. We are in the era of graphs. Graphs are hot. Graphs deliver it in spades. Over the last few years, a number of new graph databases came to market. As we start the next decade, dare we say […].

Data Integration 119

Data Integration Marketing Analytics Data Architecture 119

erwin

DECEMBER 12, 2019

erwin Data Intelligence (erwin DI) combines data management and data governance processes in an automated flow. Additionally, erwin DI is part of the larger erwin EDGE platform that integrates data modeling , enterprise architecture , business process modeling , data cataloging and data literacy.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

FEBRUARY 20, 2023

This certification requires deep understanding of Salesforce features and functionality, as well as the ability to model a role hierarchy, data model, and appropriate sharing mechanisms. The certification emphasizes testing, governance, and integration with external systems within an organization’s infrastructure.

Consulting 87

Consulting B2B Cost-Benefit Sales 87

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models.

Cost-Benefit 71

Cost-Benefit Data Integration Data Architecture Manufacturing 71

erwin

DECEMBER 12, 2019

erwin Data Intelligence (erwin DI) combines data management and data governance processes in an automated flow. Additionally, erwin DI is part of the larger erwin EDGE platform that integrates data modeling , enterprise architecture , business process modeling , data cataloging and data literacy.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

BizAcuity

MAY 24, 2022

This is done to gain better visibility of the operations, and capture data points of interest for the clients. Reasons may vary from business to business but integration is the cornerstone for customer success. With cloud data integration, it gets easier to make reports across departments and data storage will never be an issue.

Data-driven 52

Data-driven Cost-Benefit Digital Transformation Strategy 52

Cloudera

FEBRUARY 15, 2024

Cultural shift and technology adoption: Traditional banks and insurance companies must adapt to the emergence of fintech firms and changing business models. Seeing the future in a modern data architecture The key to successfully navigating these challenges lies in the adoption of a modern data architecture.

Insurance 84

Insurance Data Architecture Risk Management Risk 84

BizAcuity

APRIL 6, 2022

We do see crypto as a sustainable revenue model but at the same time, we cannot ignore the fact that at present, cryptocurrencies are extremely volatile and a slump in crypto prices could affect casino revenue adversely. Gaming enthusiasts are seeing the perks offered by NFT games DEALI including passive income through gaming.

Data Analytics 52

Data Analytics Analytics B2B Deep Learning 52

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111

Ontotext

JANUARY 10, 2024

In Computer Science, we are trained to use the Okham razor – the simplest model of reality that can get the job done is the best one. And each of these gains requires data integration across business lines and divisions. We call this the Bad Data Tax. So, how to manage this complexity better?

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

CIO Business Intelligence

MARCH 6, 2024

SAP unveiled Datasphere a year ago as a comprehensive data service, built on SAP Business Technology Platform (BTP), to provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

Unstructured Data 129

Unstructured Data Dashboards Business Intelligence Data Governance 129

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 86

Management Metadata Data Architecture Data Lake 86

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. Simplify data management . 1: Multi-function analytics . 1: Multi-function analytics .

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

Ontotext

FEBRUARY 7, 2024

However, what we usually don’t talk about when generating an asset, are the huge invisible or unplanned costs occurring at a later stage when the data needs to be made available for analysis or secondary usage. As a result, a big portion of the IT capacity in Pharma is bound by data integration.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

CIO Business Intelligence

APRIL 5, 2022

Only modern data warehouses can handle integrations for this data at speed and scale. This is most evident in the move from extract-transform-load (ETL) models to extract-load-transform (ELT) approaches. Simplifying analytics workflows.

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

IBM Big Data Hub

JANUARY 17, 2023

Regardless of size, industry or geographical location, the sprawl of data across disparate environments, increase in velocity of data and the explosion of data volumes has resulted in complex data infrastructures for most enterprises. The result is more useful data for decision-making, less hassle and better compliance.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. The reality of LLMs and other “narrow” AI technologies is that none of them is turn-key.

Insurance 79

Insurance Risk Data-driven Finance 79

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

AWS Big Data

NOVEMBER 29, 2023

Maximize value with comprehensive analytics and ML capabilities “Amazon Redshift is one of the most important tools we had in growing Jobcase as a company.” – Ajay Joshi, Distinguished Engineer, Jobcase With all your data integrated and available, you can easily build and run near real-time analytics to AI/ML/Generative AI applications.

Data Warehouse 108

Data Warehouse Data Lake Analytics Machine Learning 108

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. Bad Data Tax and the Data Bill of Rights So far, our discussion has been pretty theoretical, so we need a compelling business justification for moving in this direction.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

IBM Big Data Hub

JUNE 28, 2023

Processing terabytes or even petabytes of increasing complex omics data generated by NGS platforms has necessitated development of omics informatics. The next step in the data journey is performing analytics on the ingested data and streamlining the output in interoperability-ready formats with reproducible and scalable pipelines.

Informatics 66

Informatics Consulting Cost-Benefit Data Architecture 66

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

Data Strategy 74

Data Strategy Strategy Data Warehouse Prescriptive Analytics 74

Andrew White

JANUARY 9, 2022

Data mesh seems to mean a network of systems and hubs connected to help cope with silos. Perhaps a data mesh is what a pure architecture might design. I would suggest that one way to explore it is to explore the idea of a standard operating model. So a wide experience helps, and one that has a business angle too.

Analytics 64

Analytics Measurement Modeling Data-driven 64

IBM Big Data Hub

SEPTEMBER 12, 2022

In August the Federal Trade Commission (FTC) released an Advance Notice of Proposed Rulemaking (ANPRM) titled Commercial Surveillance and Data Security that encompasses a wide range of data protection and privacy issues, including data monetization models, discrimination and algorithmic biases and data security, to name a few.

Metadata 97

Metadata Data Governance Enterprise Data Architecture 97

Alation

JULY 28, 2022

What Are the Biggest Drivers of Cloud Data Warehousing? It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. Migration leaders would be wise to filter out data, not to migrate via a clear policy.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

BI-Survey

AUGUST 21, 2020

The primary modernization approach is data warehouse/ETL automation, which helps promote broad usage of the data warehouse but can only partially improve efficiency in data management processes. However, an automation approach alone is of limited usefulness when data management processes are inefficient.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Ontotext

MAY 30, 2019

There are two reasons for this: First, Linked Data, or, to put it in Plain English, the practice of explaining the meaning of content to machines, is essentially about linking content to semantically modeled data. Second, Linked Data is creating highly connected, computer-processable definitions of entities.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87