erwin

MAY 14, 2021

Accelerating the retrieval and analysis of data —so much of it unstructured—is vital to becoming a data-driven business that can effectively respond in real time to customers, partners, suppliers and other parties, and profit from these efforts. The Newest Release of erwin Data Modeler.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

CIO Business Intelligence

MAY 14, 2024

Controlling escalating cloud and AI costs and preventing data leakage are the top reasons why enterprises are eying hybrid infrastructure as their target AI solution. Enterprises need to ensure that private corporate data does not find itself inside a public AI model,” McCarthy says.

IT 143

IT Data Processing Enterprise Modeling 143

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. Business intelligence analyst job requirements BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

erwin

APRIL 4, 2022

If you’re a long-time erwin ® Data Modeler by Quest ® customer, you might be asking yourself, “What happened to the release naming convention of erwin Data Modeler?” In 2021 erwin Data Modeler released 2021R1. What’s new in erwin Data Modeler R12.0? DevOps GitHub integration via Mart.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. The problem is even more magnified in the case of structured enterprise data.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

DataKitchen

APRIL 28, 2021

This is happening to the term “data fabric.” Tools vendors are creating their own definitions of “data fabric” to promote their own product and solution offerings. If you search the Internet for a definition of data fabrics you can see discussions of storage, AI augmentation, and other tools.

Statistics 246

Statistics Optimization Technology Data Analytics 246

DataKitchen

DECEMBER 9, 2022

DataOps involves close collaboration between data scientists, IT professionals, and business stakeholders, and it often involves the use of automation and other technologies to streamline data-related tasks. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

CIO Business Intelligence

JANUARY 24, 2024

With nearly 800 locations, RaceTrac handles a substantial volume of data, encompassing 260 million transactions annually, alongside data feeds from store cameras and internet of things (IoT) devices embedded in fuel pumps. Their large language models have poor or dirty data.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 220

Machine Learning Risk Management Statistics 220

DataRobot Blog

FEBRUARY 16, 2022

“Integrated healthcare” has become a bit of a buzzword as of late, but no one has settled on just one definition for the term. A 2016 paper that sought to explain integrated care , laid out four different definitions and five different conceptual frameworks. Check out some of our current use cases. More information.

Machine Learning 52

Machine Learning Reporting Metrics Data Integration 52

CIO Business Intelligence

MARCH 16, 2022

We are all familiar with the EMR (electronic medial records) adoption and maturity models designed by HIMSS (Healthcare Information and Management Systems Society). But honestly speaking, there exists no unique maturity model which measures the degree of digital transformation. But it is the future of care delivery beyond boundaries.

Technology 115

Technology Digital Transformation Business Intelligence Data Warehouse 115

AWS Big Data

JUNE 6, 2023

You can then augment recommendations with out-of-the-box data quality rules. The following table lists the rules that are supported by AWS Glue Data Quality as of writing. For an up-to-date list, refer to Data Quality Definition Language (DQDL). Useful for customers to compare if all data is ingested from source systems.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

Ontotext

AUGUST 22, 2023

Worse, and according to Gartner, upward of 80% of enterprise data today is unstructured which further exacerbates the loss of knowledge, insights, and the wisdom needed to make effective business choices. As a result, organizations are looking for fresh data integration approaches to challenge the mindset with which we created them.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

Alation

JANUARY 20, 2022

This starts by determining the critical data elements for the enterprise. These items become in scope for the data quality program. Step 2: Data Definitions. Here each critical data element is described so there are no inconsistencies between users or data stakeholders. Step 4: Data Sources.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

IBM Big Data Hub

JULY 12, 2023

Lack of Standardization: GKN Aerospace’s global manufacturing business encompassed diverse products, business lines, and site operations, necessitating standardization to align FP&A models and reporting structures. Herring states, “Here’s an Excel-type model on the web, and everybody naturally understands how to use it.”

Manufacturing 64

Manufacturing Finance Sales Cost-Benefit 64

FineReport

MARCH 24, 2021

We’re living in a world where data is proliferating, and the traditional way of storing and displaying data may cause you to lose your way. However, thanks to the improvement of information technology and the birth of the browser/server model, Web Reports appear with unprecedented advantages. What is Web Report?

Reporting 98

Reporting Dashboards Interactive Visualization 98

Andrew White

DECEMBER 4, 2019

This acquisition followed another with Mulesoft, a data integration vendor. I heard some interesting stuff: Historically firms had an inside-out view of their market, and this led to organizational silos, data silos etc. Analytics offerings are valuable; data integration tools are too.

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

Ontotext

JULY 13, 2023

Knowledge graphs have greatly helped to successfully enhance business-critical enterprise applications, especially those where high performance tagging and agile data integration is needed. The customer and employee experience when using an application is key for companies to have a real impact on their processes and results.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

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

FineReport

JULY 16, 2021

In addition, data warehouse provides a data storage environment where data onto multiple data sources will be ETLed(Extracted, Transformed, Dunked) , cleaned up, and stored on a specific topic, indicating powerful data integration and maintenance capabilities of BI. Data Analysis. Free Download.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Octopai

JULY 17, 2022

destination fields may contain no more than 10 characters) Frequency of transfer for data integration cases (e.g. transfer data from source to target every 12 hours). If you’re aiming for uninterrupted data flow and accurate data, thorough data mapping is a critical piece of the puzzle.

Machine Learning 84

Machine Learning Visualization Enterprise Software 84

Smarten

JANUARY 3, 2019

These business users have adopted business intelligence and advanced analytical tools to gather and analyze data from varied data sources and use that analysis to identify the root cause of problems, identify opportunities, solve problems and share crucial data to support business decisions.

Business Intelligence 40

Business Intelligence Statistics Interactive Reporting 40

IBM Big Data Hub

JULY 26, 2023

In this blog post, we will delve into the concept of zero-based budgeting, exploring its definition, advantages, disadvantages, implementation steps, and tools needed. These tools provide a centralized platform for top-down and bottom-up budgeting creation, collaboration, scenario modeling, data integration, and reporting.

Cost-Benefit 60

Cost-Benefit Optimization Visualization Data-driven 60

Ontotext

NOVEMBER 25, 2021

With the great data integration powers of GraphDB, LAZY has achieved a lot. But now the bottleneck moves from data processing towards data gathering. Data virtualization with ONTOP. This GraphDB-native solution allows you to map relational data to RDF. However, perhaps you want to integrate relational data.

Visualization 98

Visualization Interactive Data-driven Enterprise 98

Domino Data Lab

APRIL 3, 2019

Look toward the evolving changes in system architecture to understand where data governance will be heading. Definition and Descriptions. We’ll start with standard definitions – the currently accepted wisdom in the industry. That definition plus the one-liner provide good starting points. In other words, #adulting.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

FineReport

JANUARY 5, 2022

Definition. Analytics report analyzes and evaluates a business strategy or process using qualitative and quantitative company data. As a result, it can empower employees to make data-driven decisions based on evidence and analysis. Analytics Report: Definite Guide You Will Ever Need shows at FineReport first. Conclusion.

Reporting 52

Reporting Analytics Visualization Dashboards 52

Alation

FEBRUARY 13, 2020

This achievement is a testament not only to our legacy of helping to create the data catalog category but also to our continued innovation in improving the effectiveness of self-service analytics. A broader definition of Business Intelligence. Enabling workers to find the right data is crucial to promoting self-service analytics.

Business Intelligence 52

Business Intelligence Machine Learning Marketing Metadata 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

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. Graph-based solutions further leverage the relationships among the entities involved to create a semantically enhanced machine learning model. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. E-commerce giants like Alibaba and Amazon extensively use big data to understand the market. Unlike traditional databases, processing large data volumes can be quite challenging. Easy implementation.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

erwin

JANUARY 11, 2019

The sad truth is that high-paid knowledge workers like data scientists spend up to 80 percent of their time finding and understanding source data and resolving errors or inconsistencies, rather than analyzing it for real value. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

Ontotext

JANUARY 6, 2021

A knowledge graph provides centralized information control for enterprises at a time when it is no longer possible to integrate all transactional information due to its extreme volume, velocity and variety.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

BizAcuity

APRIL 6, 2022

There is no definite answer. 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. Sounds like a win-win situation.

Data Analytics 52

Data Analytics Analytics B2B Deep Learning 52

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80