DataKitchen

JUNE 21, 2024

Navigating the Storm: How Data Engineering Teams Can Overcome a Data Quality Crisis Ah, the data quality crisis. It’s that moment when your carefully crafted data pipelines start spewing out numbers that make as much sense as a cat trying to bark. You’ve got yourself a recipe for data disaster.

Data Quality 130

Data Quality Measurement Metrics Data Collection 130

CIO Business Intelligence

NOVEMBER 27, 2024

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

TDAN

FEBRUARY 21, 2024

Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy.

Data Quality 105

Data Quality Data Governance Strategy IT 105

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 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

DataKitchen

MAY 7, 2024

DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certificatio n (3 hours, online, free, signup online): DataOps Manifesto (over 30,000 signatures) One (..)

Data Quality 161

Data Quality Testing Metrics Consulting 161

O'Reilly on Data

JULY 15, 2019

Regulators behind SR 11-7 also emphasize the importance of data—specifically data quality , relevance , and documentation. While models garner the most press coverage, the reality is that data remains the main bottleneck in most ML projects.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 97

Data Quality Data-driven Data Lake Metrics 97

O'Reilly on Data

JUNE 18, 2019

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

CIO Business Intelligence

FEBRUARY 26, 2025

But when an agent whose primary purpose is understanding company documents and tries to speak XML, it can make mistakes. If an agent needs to perform an action on an AWS instance, for example, youll actually pull in the data sources and API documentation you need, all based on the identity of the person asking for that action at runtime.

IT 141

IT Enterprise Interactive Data Quality 141

CIO Business Intelligence

MARCH 25, 2025

Data debt that undermines decision-making In Digital Trailblazer , I share a story of a private company that reported a profitable year to the board, only to return after the holiday to find that data quality issues and calculation mistakes turned it into an unprofitable one.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

O'Reilly on Data

MARCH 24, 2020

” One of his more egregious errors was to continually test already collected data for new hypotheses until one stuck, after his initial hypothesis failed [4]. You may picture data scientists building machine learning models all day, but the common trope that they spend 80% of their time on data preparation is closer to the truth.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

AWS Big Data

NOVEMBER 22, 2024

This makes sure your data models are well-documented, versioned, and straightforward to manage within a collaborative environment. Compliance and data governance – For organizations managing sensitive or regulated data, you can use Athena and the adapter to enforce data governance rules.

Data Lake 102

Data Lake Data Warehouse Cost-Benefit Data Transformation 102

Ontotext

MAY 26, 2021

In natural language processing (NLP) and computational linguistics the Gold Standard typically represents a corpus of text or a set of documents, annotated or tagged with the desired results for the analysis – be it designation of the corresponding part of speech, syntactic parsing, concept or relationship.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

Ontotext

NOVEMBER 16, 2023

In the first part of this series of technological posts, we talked about what SHACL is and how you can set up validation for your data. Tacking the data quality issue — bit by bit or incrementally There are two main approaches to validating your data, which would be dependent on the specific implementation.

Data Quality 69

Data Quality Reporting Testing Technology 69

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. The insights are used to produce informative content for stakeholders (decision-makers, business users, and clients).

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

CIO Business Intelligence

SEPTEMBER 12, 2024

An aircraft engine provider uses AI to manage thousands of technical documents required for engine certification, reducing administration time from 3-6 months to a few weeks. Assess and address data quality Once your data is centralized and cataloged, assessing and addressing data quality standards is crucial.

Unstructured Data 119

Unstructured Data Data Quality Structured Data Machine Learning 119

Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence. Conclusion.

Data Quality 139

Data Quality Machine Learning Digital Transformation Big Data 139

CIO Business Intelligence

FEBRUARY 6, 2025

When youre dealing with truly complex, unstructured data like text, voice and images. Think sentiment analysis of customer reviews, summarizing lengthy documents or extracting information from medical records. Theyre also useful for dynamic situations where data and requirements are constantly changing.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

O'Reilly on Data

NOVEMBER 28, 2023

And there are tools for archiving and indexing prompts for reuse, vector databases for retrieving documents that an AI can use to answer a question, and much more. Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3% report that the difficulty of training a model is a problem.

Enterprise 342

Enterprise Testing Modeling Reporting 342

Rocket-Powered Data Science

FEBRUARY 15, 2023

Since ChatGPT is built from large language models that are trained against massive data sets (mostly business documents, internal text repositories, and similar resources) within your organization, consequently attention must be given to the stability, accessibility, and reliability of those resources.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Data-related decisions, processes, and controls subject to data governance must be auditable.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

APRIL 8, 2025

Concurrent UPDATE/DELETE on overlapping partitions When multiple processes attempt to modify the same partition simultaneously, data conflicts can arise. For example, imagine a data quality process updating customer records with corrected addresses while another process is deleting outdated customer records.

Snapshot 136

Snapshot Management Metadata Big Data 136

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

Smart Data Collective

SEPTEMBER 26, 2021

A NoSQl database can use documents for the storage and retrieval of data. The central concept is the idea of a document. Documents encompass and encode data (or information) in a standard format. A document is susceptible to change. The documents can be in PDF format. Speaking of which.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

CIO Business Intelligence

JUNE 5, 2024

Crucial data resides in hundreds of emails sent and received every day, on spreadsheets, in PowerPoint presentations, on videos, in pictures, in reports with graphs, in text documents, on web pages, in purchase orders, in utility bills, and on PDFs. That data is free flowing and does not reside in one place.

Management 142

Management Strategy Data Strategy Marketing 142

erwin

APRIL 29, 2020

In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates. Business terms and data policies should be implemented through standardized and documented business rules.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

CIO Business Intelligence

SEPTEMBER 10, 2024

This AI-augmented approach ensures that no critical feature falls through the cracks and that accurate requirements documents reduce the likelihood of defects. Invest in data quality: GenAI models are only as good as the data they’re trained on -with GenAI, mistakes can be amplified at speed. Result: 80% less rework.

Software 124

Software Digital Transformation Testing Advertising 124

Ontotext

NOVEMBER 23, 2023

This technique can be especially useful in data integration projects where you are combining related, potentially overlapping data from multiple sources. Remember to set up your shapes graph in a repository that has been configured from the beginning to support SHACL, as described in our documentation.

Data Quality 69

Data Quality Reporting Metadata Big Data 69

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

CIO Business Intelligence

DECEMBER 11, 2024

The field of data observability has experienced substantial growth recently, offering numerous commercial tools on the market or the option to build a DIY solution using open-source components. Data governance needs to follow a similar path, transitioning from policy documents and confluence pages to data policy as code.

Management 111

Management Data Governance Data Science Reporting 111

DataKitchen

FEBRUARY 23, 2024

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 117

Testing Data-driven Data Quality Metrics 117

CIO Business Intelligence

MAY 2, 2023

Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality.

Digital Transformation 141

Digital Transformation IT Data-driven Data Quality 141

datapine

APRIL 16, 2019

The cost of waiting to see what happens is well documented…. 8) Present the data in a meaningful way. Rob Enderle, a former IBM employee and Research Fellow for Forrester wrote a fabulous article which documents the shortcomings of executives at IBM and Microsoft.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

Smarten

DECEMBER 17, 2024

According to a recent TechJury survey: Data analytics makes decision-making 5x faster for businesses. The top three business intelligence trends are data visualization, data quality management, and self-service business intelligence (BI). 7 out of 10 business rate data discovery as very important.

Reporting 52

Reporting Key Performance Indicator KPI Business Intelligence 52

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110