erwin

MARCH 17, 2020

Here are a few examples specific to enterprise architecture and business process modeling, data modeling and data governance. erwin Data Modeler can help you find, visualize, design, deploy and standardize high-quality enterprise data assets. Data Governance. Building in the cloud? No problem.

Data Governance 138

Data Governance Enterprise Modeling Metadata 138

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. In some ways, the data architect is an advanced data engineer.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Octopai

JUNE 24, 2019

There are a number of scenarios that necessitate data governance tools. Businesses operating within strict industry regulations, utilizing analytics software, and/or regularly consolidating data in key subject areas will find themselves looking into data governance tools to help them achieve their goals.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. Being able to integrate all data touchpoints, including erwin DM for data modeling, Denodo for data visualization, and Jira for ticketing, has been key.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

erwin

FEBRUARY 28, 2024

One of the key ingredients to ensure data is really embedded in an organization, and one of the key enablers to increase the strategic impact of data, is the setup of a successful data governance program. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool.

Metadata 52

Metadata Data Governance Data Quality Technology 52

erwin

MARCH 30, 2020

To do this, the consortium will need the ability to automatically scan and catalog the data sources and apply strict data governance and quality practices. Unraveling Data Complexities with Metadata Management. Metadata management will be critical to the process for cataloging data via automated scans.

Metadata 122

Metadata IT Data Governance Data Quality 122

DataKitchen

JANUARY 5, 2021

Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. Each of the roles mentioned above views the world through a preferred set of tools: Data Center/IT – Servers, storage, software.

Testing 147

Testing Data Governance Metadata Visualization 147

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. Who are the data owners?

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Who are the data owners? Five Consequences of Ignoring Data Lineage.

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

Octopai

JUNE 27, 2022

Your most technologically-challenged business user searches the data catalog at least once a week – without coming to you for help! Data catalog SUCCESS! Visualization may work wonders for athlete performance, but if you want to make data catalog adoption into a rousing success, you’re going to sweat a little bit.

Management 72

Management Metadata Visualization Data Governance 72

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

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

Octopai

APRIL 24, 2023

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

Cost-Benefit 96

Cost-Benefit Data-driven Data Warehouse Data Governance 96

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

erwin

AUGUST 6, 2020

Good Data = Good Decisions. Without good data, it’s difficult to make good decisions. Data access, literacy and knowledge leads to sound decision-making and that’s key to data governance and any other data-driven effort. Data literacy enables collaboration and innovation.

Contextual Data 135

Contextual Data Data Governance Digital Transformation Metadata 135

datapine

SEPTEMBER 29, 2022

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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 69

Analytics Data Warehouse Data Lake Metadata 69

erwin

SEPTEMBER 6, 2021

To combat dark data and shine a light on available data, many organizations are turning to data intelligence software. Impact analysis capabilities within data intelligence software additionally arm IT with the visibility needed to better understand potential change, proactively avoid landmines and make best-interest decisions.

Enterprise 52

Enterprise Data Governance Dashboards Visualization 52

Alation

JUNE 22, 2021

The first post in the series defines data culture , its benefits, and the three pillars of data culture. The second and fourth posts take a deeper look at data search & discovery and data governance, respectively. What is Data Literacy? WARNING: if you teach people how to persuade with data (e.g.

Data Governance 64

Data Governance Data-driven Metadata Visualization 64

Alation

SEPTEMBER 21, 2021

It is people, process, technology, and data — more importantly, metadata. Metadata provides technical and behavioral intelligence about data that can be used to decide where to start and how to plot a course to the destination, including who needs to be involved and who can offer assistance if roadblocks are encountered.

Metadata 52

Metadata Testing Recreation/Entertainment Data-driven 52

Octopai

APRIL 5, 2020

The solution to such problems is automated BI intelligence – a comprehensive platform that includes automated data lineage, data discovery, and business glossary. Octopai empowers users with visual maps that are comprehensive in their ability to explain data from various angles and to trace a data point from source to endpoint.

Metadata 52

Metadata Data Quality Reporting Management 52

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. How Data Lineage Is a Use Case in ML. Data lineage is one example of a use case in which ML can play a pivotal role.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Cloudera

AUGUST 26, 2021

This means that there is out of the box support for Ozone storage in services like Apache Hive , Apache Impala, Apache Spark, and Apache Nifi, as well as in Private Cloud experiences like Cloudera Machine Learning (CML) and Data Warehousing Experience (DWX). Data ingestion through ‘s3’. Data processing and visualization.

Data Science 108

Data Science Forecasting Metadata Machine Learning 108

Alation

FEBRUARY 13, 2020

A typical data catalog implementation process begins by defining the business and technical case, proceeds through technology selection and installation, then moves on to data discovery and populating the metadata catalog. Figure 1 – Data Catalog Implementation. Will data stewards assume curation responsibilities?

Metadata 52

Metadata Data Governance Cost-Benefit Visualization 52

Octopai

JULY 9, 2020

Here are some scenarios in which companies found real benefits from automated data lineage solutions: Data Lineage Enables Complex Data Processing Operations. By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

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

erwin

OCTOBER 29, 2020

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. Data readiness depends on automation to create the data pipeline. We asked participants to “talk to us about data value chain bottlenecks.”

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

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

IBM Big Data Hub

MAY 9, 2022

As for data delivery at the “right time” automated data engineering tasks, workload balancing and elastic scaling should provide the needed alacrity for all businesses. Data governance and privacy. Automated metadata generation is essential in order to turn a manual process into one that is better controlled.

Management 57

Management Data Quality Metadata Data Integration 57

Alation

FEBRUARY 20, 2020

These recommendations organize the data about your data — what the industry for many years has called metadata. And yet instead of storing this metadata in a vault accessible only by IT experts, Alation makes metadata come alive as a living data recommendation engine for the business.

Metadata 52

Metadata Analytics Dashboards Sales 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

Octopai

FEBRUARY 9, 2023

Trying to manage data governance without a comprehensive data lineage solution can leave you feeling like your data keeps running away. It’s not easy to keep up with data and metadata on the move. A comprehensive data lineage tool is the secret weapon of successful data governance managers and data stewards.

Data Governance 52

Data Governance Metadata Data Quality Management 52

Alation

MAY 4, 2023

Are you an aspiring data scientist , or just want to understand the benefits of integrating data catalogs with visualization tools? In today’s ever-growing world of data, having an easy way to gain insights quickly is essential. What are data visualization tools?

Visualization 52

Visualization Metadata Data Governance KPI 52

erwin

OCTOBER 4, 2021

Metadata management is essential to becoming a data-driven organization and reaping the competitive advantage your organization’s data offers. Gartner refers to metadata as data that is used to enhance the usability, comprehension, utility or functionality of any other data point. How the data has changed.

Metadata 52

Metadata Software Management Visualization 52

erwin

FEBRUARY 12, 2021

Because that is where the GRC and data layers meet. Processes produce, process and consume data –information captured in the metadata layer. By following the process sequence, I can actually trace the data lineage as it flows across the entire business ecosystem, beyond the application layer.

Risk 98

Risk Slice and Dice Management Enterprise 98