erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Octopai

JANUARY 19, 2020

It will not surprise you to learn all 11 of the bank-relevant principles are related to data in some form or fashion. Here’s a sampling: – Principle 1 covers data governance, including “a firm’s policies on data confidentiality, integrity, and availability, as well as risk-management policies.”.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

datapine

SEPTEMBER 29, 2022

Therefore, there are several roles that need to be filled, including: DQM Program Manager: The program manager role should be filled by a high-level leader who accepts the responsibility of general oversight for business intelligence initiatives. The program manager should lead the vision for quality data and ROI.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Octopai

APRIL 5, 2020

How much time are you spending on manual data mapping? And how much time are you investing in other manual data procedures such as data discovery? The solution to such problems is automated BI intelligence – a comprehensive platform that includes automated data lineage, data discovery, and business glossary.

Metadata 52

Metadata Data Quality Reporting Management 52

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data. In terms of data lineage, they offer an excellent definition here. .

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. The MDM tool should help with this.

Management 52

Management Data Quality Metadata Testing 52

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 130

IT Business Intelligence Sales Key Performance Indicator 130

erwin

MAY 27, 2020

And it exists across these hybrid architectures in different formats: big and unstructured and traditional structured business data may physically sit in different places. What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. 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

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Alation

OCTOBER 21, 2021

Data lakes also support the growing thirst for analysis by data scientists and data analysts, as well as the critical role of data governance. But setting up a data lake takes a thoughtful approach to ensure it’s positioned to prevent it from becoming a data swamp. Lack of metadata.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) And that makes sense.

Cost-Benefit 82

Cost-Benefit Metadata Data Governance Modeling 82

IBM Big Data Hub

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches. Geocoding Geocoding is the process of adding location metadata to an organization’s datasets.

Data Quality 67

Data Quality Data Integration Metadata Cost-Benefit 67

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In this post: What Is a Data Model? Why Is Data Modeling Important? What Is a Data Model?

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

Jen Stirrup

MARCH 29, 2023

SAP Datasphere helps eliminate hidden data debt within organizations, enabling customers to build a business data fabric architecture that quickly delivers meaningful data with business context and logic intact. Business Intelligence is often a search problem in disguise.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

Alation

APRIL 7, 2021

A data catalog contains critical metadata (like schema information), which need to be secure and available to consumers at all times. Hence, the data catalog must be protected by enterprise-grade security. Alation possesses three unique capabilities: intelligence, active data governance, and broad, deep connectivity.

Data Governance 52

Data Governance Enterprise Metadata Cost-Benefit 52

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. Business intelligence reports. Visualizations. A data catalog unifies disparate data into a single source of information. Data Catalog by Type.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

erwin

JUNE 27, 2019

Empower employees with self-service access for enterprise data capability, fluency and accountability. Evaluating a Data Modeling Tool – Key Features. Organizations seeking to invest in a new data modeling tool should consider these four key features.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

Alation

FEBRUARY 13, 2020

Gartner: Magic Quadrant for Metadata Management Solutions. Magic Quadrant for Metadata Management Solutions 4 based on its ability to execute and completeness of vision. Today, metadata management has become a critical business driver as data leaders seek to govern and maximize the value from the influx of data at their disposal.

Metadata 52

Metadata Machine Learning Data Governance Reporting 52

BI-Survey

MARCH 4, 2022

Organizations that are still early in the process of shaping their data culture seem to fare better when focusing their strategy on establishing a data democracy. More than a third of them have planned specific initiatives for data governance and data access. DATA LEADERSHIP. DATA GOVERNANCE.

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. Provide and keep up to date with technical metadata for loaded data.

Dashboards 100

Dashboards Data-driven Publishing Cost-Benefit 100

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Alation

FEBRUARY 20, 2020

After investing in self-service analytic tooling, organizations are now turning their attention to linking infrastructure and tooling to data-driven decisions. The Forrester Wave : Machine Learning Data Catalogs, Q2 2018. But as the category gains greater recognition, more companies are building data catalog solutions.

Machine Learning 52

Machine Learning Marketing Reporting ROI 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

BI-Survey

FEBRUARY 6, 2020

ML helps users prepare data to enhance reports and to select appropriate data visualizations in visual analysis and dashboards. Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data. Maintain a comprehensive data catalog to make data treasures easy to find.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 85

Data Lake Data Warehouse B2B Data-driven 85

Jet Global

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 14, 2024

The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. Data Transformation and Modeling Jet’s low-code environment lets your users transform and model their data within Fabric, making data preparation for analysis easy.

Analytics 52

Analytics Management Reporting Enterprise 52