erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Business terms and data policies should be implemented through standardized and documented business rules.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Organizations still depend too much on manual data management.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

Smart Data Collective

JULY 15, 2021

It helps you locate and discover data that fit your search criteria. With data catalogs, you won’t have to waste time looking for information you think you have. What Does a Data Catalog Do? This means that they can be ideal for data cleansing and maintenance. What Does a Data Catalog Consist Of?

Metadata 125

Metadata IT Data-driven Data Quality 125

CIO Business Intelligence

JANUARY 9, 2024

He and his team have created information decks, documents, and presentations that describe the various types of AI and how they can be used and explain how and where AI and machine learning may be useful — and why it’s not the solution to all the problems they have. Can the current state of our data operations deliver the results we seek?

IT 136

IT Risk Cost-Benefit Enterprise 136

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 73

Data Quality Data Lake Data-driven Metrics 73

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

erwin

JANUARY 17, 2019

It assists in successfully meeting increasingly strict compliance requirements, such as those in the General Data Protection Regulation (GDPR). A mature and sustainable data governance initiative must include data integration. And it provides a clear gauge on business performance.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Alation

JUNE 2, 2022

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. However, governance processes are equally important. Conclusion.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Cloudera

AUGUST 31, 2021

Leveraged delivery accelerators as well as a Data Quality framework customized by the client. The centralized complete views of verified and data-quality validated source system data within the Data Fabric helped the client streamline both security and data integration efforts across their internal application footprint.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Ontotext

JANUARY 6, 2021

Reuse of knowledge from third party data providers and establishing data quality principles to populate it. Ontotext worked with a global research-based biopharmaceutical company to solve the problem of inefficient search across dispersed and vast sources of unstructured data.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

FineReport

APRIL 26, 2023

MongoDB MongoDB, which gained popularity in 2010, is a NoSQL document-oriented database platform that is free and open-source. It uses collections and documents to store a high volume of data, with documents consisting of key-value pairs as the basic unit. It supports master-slave replication for data backup.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Ontotext

JUNE 10, 2021

They should be able to continuously integrate data across multiple internal systems and link it to data from external sources. Further, “ML-Augmented data integration is making active metadata analysis and semantic knowledge graphs pivotal parts of the data fabric””.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

Andrew White

NOVEMBER 14, 2022

If you are at risk of not knowing where high risk data is, such as personally identifiable information (PII) in support of privacy regulations, then a data catalog – or more precisely a data discovery tool – is useful. If not, a data catalog won’t be needed for at least 9 months. Do What I Do, Not What I Say.

Data Integration 52

Data Integration Technology Data Governance Analytics 52

Jet Global

MAY 1, 2020

We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Data quality issues. Here’s the ugly truth: Everybody has a data quality problem. This is because people won’t use BI applications that are founded on irrelevant, incomplete, or questionable data.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

Peter James Thomas

SEPTEMBER 19, 2018

The peterjamesthomas.com Data and Analytics Dictionary is an active document and I will continue to issue revised versions of it periodically. Data Asset. Data Audit. Data Classification. Data Consistency. Data Controls. Data Curation (contributor: Tenny Thomas Soman ). Data Democratisation.

Analytics 45

Analytics Testing Data Strategy Data Integration 45

O'Reilly on Data

DECEMBER 12, 2019

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8].

Machine Learning 197

Machine Learning Modeling Testing Risk Management 197

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. Use Case #6: Data Quality and Governance The size and complexity of data sources and datasets is making traditional data dictionaries and Entity Relationship Diagrams (ERD) inadequate.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 77

Enterprise Data Integration Data Quality Contextual Data 77

erwin

FEBRUARY 19, 2021

It involves establishing policies and processes to ensure information can be integrated, accessed, shared, linked, analyzed and maintained across an organization. Better data quality. It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

CIO Business Intelligence

FEBRUARY 20, 2023

A candidate who earns the certification will have proved their ability to build bundle configurations, pricing, output documents, and renewals and amendments.

Consulting 70

Consulting B2B Cost-Benefit Sales 70

erwin

FEBRUARY 4, 2021

It uncovered a number of obstacles that organizations have to overcome to improve their data operations. 1 bottleneck, according to 62 percent of respondents, was documenting complete data lineage. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

erwin

FEBRUARY 6, 2020

How to Automate Data Management. Here are our eight recommendations for how to transition from manual to automated data management: 1) Put Data Quality First: Automating and matching business terms with data assets and documenting lineage down to the column level are critical to good decision making.

Management 144

Management Data Governance Cost-Benefit Metadata 144

Cloudera

SEPTEMBER 7, 2023

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Systematize governance. Create core feedback mechanisms.

Insurance 79

Insurance Risk Data-driven Modeling 79

Cloudera

APRIL 14, 2021

Precisely Data Integration, Change Data Capture and Data Quality tools support CDP Public Cloud as well as CDP Private Cloud. Data pipelines that are bursty in nature can leverage the public cloud CDE service while longer running persistent loads can run on-prem.

Data Warehouse 80

Data Warehouse Data Processing Data Quality Machine Learning 80

erwin

MAY 27, 2020

They should automatically generate data models , providing a simple, graphical display to visualize a wide range of enterprise data sources based on a common repository of standard data assets through a single interface. Data governance should be integrated throughout the data modeling process.

Modeling 98

Modeling Metadata Data Governance Visualization 98

IBM Big Data Hub

OCTOBER 12, 2023

Documentation can also be generated and maintained with information such as a model’s data origins, training methods and behaviors. Security and privacy —When all data scientists and AI models are given access to data through a single point of entry, data integrity and security are improved.

Cost-Benefit 81

Cost-Benefit Metadata Data Governance Modeling 81

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

JULY 29, 2021

17 years later, in the third edition of The Semantic Web for the Working Ontologist , authors Dean Allemang, Hedler and Gandon covered these same perspectives with one distilled explanation: The Semantic Web faces the problem of distributed data head-on. We can’t imagine looking at the Semantic Web as an artifact.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Andrew White

JANUARY 9, 2022

Is there a good map that shows the connections between data, advanced analytics, digital, innovation, etc. I would have to admit that there are few documents that talk about all the connections across any set of topics. Much as the analytics world shifted to augmented analytics, the same is happening in data management.

Analytics 64

Analytics Measurement Modeling Data-driven 64

CIO Business Intelligence

NOVEMBER 7, 2023

Opting for a centralized data and reporting model rather than training and embedding analysts in individual departments has allowed us to stay nimble and responsive to meet urgent needs, and prevented us from spending valuable resources on low-value data projects which often had little organizational impact,” Higginson says.

Data Warehouse 142

Data Warehouse Digital Transformation Reporting Data-driven 142

datapine

FEBRUARY 22, 2022

They can govern the implementation with a documented business case and be responsible for changes in scope. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Find a way to integrate it into the new strategy, or you will have upset employees. It’s that simple.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

erwin

MAY 17, 2021

We explored the bottlenecks and issues causing delays across the entire data value chain. Thematically “data quality” is at the heart desired data governance outcomes, challenges and bottlenecks, pointing to its overall importance. Self-service done right is a game-changer.

Data Governance 99

Data Governance Data Quality Snapshot Reporting 99

erwin

JUNE 17, 2021

We explored the bottlenecks and issues causing delays across the entire data value chain. Thematically “data quality” is at the heart of desired data governance outcomes, challenges and bottlenecks, pointing to its overall importance. Self-service done right is a game-changer.

Data Governance 59

Data Governance Data Quality Snapshot Reporting 59