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. Data integration and cleaning. Data unification and integration.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

CIO Business Intelligence

MARCH 4, 2024

Harmonizing these data sets with centralized enterprise data faces increasing challenges as shifts to data definitions, schema, and architecture require constant central data team efforts.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

CIO Business Intelligence

JANUARY 24, 2024

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 84

Metadata Data Lake Visualization Data Transformation 84

Andrew White

DECEMBER 4, 2019

I argued that one vendors’ book on data quality was really about data governance; I argued that another vendors’ marketing message was totally upside down; and I argued that some approaches to achieving single source of truth were different from traditional approaches. See Salesforce acquisition of Tableau – What does it mean?

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

Octopai

JANUARY 31, 2021

Specifically, when it comes to data lineage, experts in the field write about case studies and different approaches to this utilizing this tool. Among many topics, they explain how data lineage can help rectify bad data quality and improve data governance. . TDWI – Philip Russom. Malcolm Chisholm.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

DataKitchen

DECEMBER 9, 2022

DataOps automation typically involves the use of tools and technologies to automate the various steps of the data analytics and machine learning process, from data preparation and cleaning, to model training and deployment. By using DataOps, organizations can improve. Query> When do DataOps?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

erwin

JANUARY 11, 2019

It’s only when companies take their first stab at manually cataloging and documenting operational systems, processes and the associated data, both at rest and in motion, that they realize how time-consuming the entire data prepping and mapping effort is, and why that work is sure to be compounded by human error and data quality issues.

Data Governance 40

Data Governance Risk Metadata Management 40

Cloudera

AUGUST 31, 2021

Pulse helps in discovery and understanding the bottlenecks in existing legacy data warehouses. These schemas will be created based on its definitions in existing legacy data warehouses. Smart DwH Mover helps in accelerating data warehouse migration. Value Achieved.

Data Warehouse 85

Data Warehouse Cost-Benefit Metadata Data-driven 85

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. Reuse of knowledge from third party data providers and establishing data quality principles to populate it.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Howard Dresner

JANUARY 20, 2014

Instead, let’s kick start the year with some definite plans and aspirations of companies in the business intelligence sphere. Definitely, they responded. Another tweeted, “Through the use of location analytics organization can see new patterns in their data that graphs and charts don’t reveal.”

Business Intelligence 56

Business Intelligence Software Data Processing Marketing 56

Ontotext

MARCH 8, 2023

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

FineReport

APRIL 26, 2023

Talend Talend is an open-source data integration platform that provides a range of software and services suitable for big data, data integration, data management, data quality, cloud storage, and enterprise application integration.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

MAY 10, 2021

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214

Testing Manufacturing Data Quality Statistics 214

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 87

Optimization B2B Data Quality Sales 87

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. Automate the collection of metadata from various data management silos and consolidate it into a single source. Structure and deploy data sources. Map data flows.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Ontotext

MARCH 27, 2024

Poor data modeling capabilities of LPGs with vendor specific constructs to express semantic constraints hinders portability, expressibility, and semantic data integration. It accelerates data projects with data quality and lineage and contextualizes through ontologies , taxonomies, and vocabularies, making integrations easier.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Ontotext

JUNE 29, 2023

This standardizes your data processing across different teams and departments, reducing manual effort and improving data quality. The straightforward answer to this question is that knowledge graphs put data into context to provide a smart framework for data integration, unification, analytics and sharing.

Cost-Benefit 59

Cost-Benefit Data-driven Data Quality Enterprise 59

Ontotext

FEBRUARY 19, 2020

Although there is still no single, universally accepted definition, there have been various attempts at it – such as in Towards a Definition of Knowledge Graphs. Clean your data to ensure data quality. Correct any data quality issues to make the data most applicable to your task.

Modeling 90

Modeling Knowledge Discovery Data Quality Technology 90

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

Alation

AUGUST 11, 2022

Everybody’s trying to solve this same problem (of leveraging mountains of data), but they’re going about it in slightly different ways. Data fabric is a technology architecture. It’s a data integration pattern that brings together different systems, with the metadata, knowledge graphs, and a semantic layer on top.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

erwin

MAY 27, 2020

What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail. Visualizing data from anywhere defined by its context and definition in a central model repository, as well as the rules for governing the use of those data elements, unifies enterprise data management.

Modeling 98

Modeling Metadata Data Governance Visualization 98

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 75

Management Metadata Testing Internet of Things 75

Alation

JANUARY 13, 2022

But make no mistake: A data catalog addresses many of the underlying needs of this self-serve data platform, including the need to empower users with self-serve discovery and exploration of data products. In this blog series, we’ll offer deep definitions of data fabric and data mesh, and the motivations for each. (We

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

FineReport

MAY 25, 2023

In this article, we are going to tell you everything you need to know about HR Dashboard, including the definition, functions, useful metrics, examples, and most importantly, how to create HR Dashboard effectively by using professional dashboard software. FineReport also supports data validation, ensuring data accuracy and integrity.

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

Alation

JULY 28, 2022

Cloud data should remove the infrastructure discussions and return attention to business, data, and outcomes. With this said, Hinchcliffe summarizes the biggest cloud data migration risks as: Source/target vendor lock-in. Data quality /wrangling. Ability to move out/costs of data egress. Lower control.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Ontotext

JULY 29, 2021

We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. The two distinct threads interlacing in the current Semantic Web fabrics are the semantically annotated web pages with schema.org (structured data on top of the existing Web) and the Web of Data existing as Linked Open Data.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. Alation Data Catalog for the data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

Andrew White

JANUARY 9, 2022

Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration. I suspect there is much less Maverick to synthetic data today.

Analytics 64

Analytics Measurement Modeling Data-driven 64

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

erwin

MAY 17, 2021

Data Governance Definition Varies. There is still no consensus on how to define data governance. When asked for a definition, the two most popular responses were: Building a set of policies that governs data. Ensuring data usage follows defined rules. Key Bottlenecks and Challenges.

Data Governance 99

Data Governance Data Quality Snapshot Reporting 99

erwin

JUNE 17, 2021

Data Governance Definition Varies. There is still no consensus on how to define data governance. When asked for a definition, the two most popular responses were: Building a set of policies that governs data. Ensuring data usage follows defined rules. Key Bottlenecks and Challenges.

Data Governance 59

Data Governance Data Quality Snapshot Reporting 59

erwin

AUGUST 31, 2023

Improved Decision Making : Well-modeled data provides insights that drive informed decision-making across various business domains, resulting in enhanced strategic planning. Reduced Data Redundancy : By eliminating data duplication, it optimizes storage and enhances data quality, reducing errors and discrepancies.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361