AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

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Data Quality Data Governance Data Lake Testing 89

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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 (..)

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Data Quality Testing Consulting Metrics 161

ScienceSoft

APRIL 13, 2021

No more wrong data analysis caused by bad data! Be armed with our new blog post on data quality assurance in the context of CRM.

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Data Quality 98

Dataiku

SEPTEMBER 13, 2023

In this blog , David Talaga (Product Marketing at Dataiku) explains that shopping in a supermarket could be similar to searching for the best data product for your use case. As a data analyst, the same mechanism applies to the data products you are looking for: Can I trust it?

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Data Quality Marketing IT 85

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.

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Data Quality Reporting Testing Technology 69

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

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Data Quality Data Governance Metrics Statistics 94

AWS Big Data

JUNE 6, 2023

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

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Data Quality Data Lake Visualization Data-driven 66

TDAN

OCTOBER 18, 2022

Last week, we presented a webinar in our Data Governance — Best Practices series on data quality. Obviously, we’re a […].

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Data Quality Data Governance Data Strategy Strategy 52

Alation

MAY 24, 2022

In a sea of questionable data, how do you know what to trust? Data quality tells you the answer. It signals what data is trustworthy, reliable, and safe to use. It empowers engineers to oversee data pipelines that deliver trusted data to the wider organization. Today, as part of its 2022.2

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Data Quality Metadata Reporting Metrics 52

IBM Big Data Hub

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

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Data Quality Data Governance People Analytics Data-driven 68

IBM Big Data Hub

AUGUST 2, 2023

However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent. According to a Gartner report , poor data quality costs organizations an average of USD $12.9 What is data quality? Data quality is critical for data governance.

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Data Quality Snapshot Data Governance Data-driven 65

IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

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Data Quality Metadata Data Governance Data-driven 57

Alation

DECEMBER 7, 2021

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly. Does the quality of this dataset meet user expectations?

Data Quality 52

Data Quality Metadata Testing Data Governance 52

DataKitchen

MAY 10, 2024

Harnessing Data Observability Across Five Key Use Cases The ability to monitor, validate, and ensure data accuracy across its lifecycle is not just a luxury—it’s a necessity. Data Evaluation Before new data sets are introduced into production environments, they must be thoroughly evaluated and cleaned.

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Data Quality Dashboards Strategy Testing 141

DataKitchen

MAY 10, 2024

Data ingestion monitoring, a critical aspect of Data Observability, plays a pivotal role by providing continuous updates and ensuring high-quality data feeds into your systems. This process is critical as it ensures data quality from the onset. Ensuring all data arrives on time and is of the right quality.

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Data Quality Testing Software Dashboards 130

Ontotext

NOVEMBER 23, 2023

The next step is to get out there and challenge your data quality dragons. The post SHACL-ing the Data Quality Dragon III: A Good Artisan Knows Their Tools appeared first on Ontotext. Get GraphDB and try your hand with our examples for SHACL validation from the documentation !

Data Quality 69

Data Quality Reporting Metadata IT 69

Anmut

JULY 12, 2021

Data without context is just meaningless noise, and any effort to improve or extract value from your data without considering the larger business context is doomed to fall short.? Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem.

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Data Quality Measurement Metrics Dashboards 52

Octopai

JANUARY 31, 2021

We have identified the top ten sites, videos, or podcasts online that deal with data lineage. Our list of Top 10 Data Lineage Podcasts, Blogs, and Websites To Follow in 2021. Data Engineering Podcast. This podcast centers around data management and investigates a different aspect of this field each week.

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Data Governance Data Processing Data Quality Metadata 57

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

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Testing Metrics Data Quality Dashboards 124

Jim Harris

JANUARY 1, 2016

Lest my pith be misunderstood aplenty, this blog post provides more detail, plus links to related posts, about what I meant. 1 — Investigate Data quality is not exactly a riddle wrapped in a mystery inside an enigma. However, understanding your data is essential to using it effectively and improving its quality.

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Data Quality Data Governance Cost-Benefit ROI 61

Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? I hope that you enjoy reading this blog post, but most important, I hope you always remember: “Data are friends, not food.” Data Silos. Data Cleansing.

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Data Quality Enterprise Business Intelligence Data Governance 56

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Fast, Safe Development and Deployment (#4) Introduction The integrity and functionality of new code, tools, and configurations during the development and deployment stages are crucial. This process is critical as it ensures data quality from the onset.

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Testing Cost-Benefit Data Quality Dashboards 124

Octopai

APRIL 19, 2021

He is the President of Knowledge Integrity, Inc and an expert in master data management, data quality, and business intelligence. His articles on TDWI deal with advice for analysts, customer data profiling, master data management technology, and machine learning. . IRM UK Connects. It is published by Robert S.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

Ontotext

MAY 26, 2021

The post The Gold Standard – The Key to Information Extraction and Data Quality Control appeared first on Ontotext. White Paper: Text Analysis for Content Management. Learn how we can make your content serve you better!

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Data Quality Machine Learning Measurement Metadata 87

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’ (..)

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Testing Data-driven Metrics Data Quality 117

DataKitchen

MARCH 12, 2024

I used to be very, very careful when changing anything data-related, but I think you’re starting to see that it’s not that big a deal anymore because [if something goes wrong] we can now figure out what happened pretty quickly, and we can adjust it.“ Global Pharma Company Related Benefits Improve time to remediation.

Metrics 117

Metrics Software Cost-Benefit Testing 117

DataKitchen

FEBRUARY 27, 2024

However, the foundation of their success rests not just on sophisticated algorithms or computational power but on the quality and integrity of the data they are trained on and interact with. The Imperative of Data Quality Validation Testing Data quality validation testing is not just a best practice; it’s imperative.

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Data Quality Unstructured Data Testing Modeling 117

DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

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Data Quality Testing Data Lake Data Integration 136

Timo Elliott

MAY 19, 2023

The integration of these solutions with SAP MDG has resulted in significant process efficiencies, a 60% increase in overall data quality, and a 75% decrease in process variants through simplification and consolidation. This shift has enabled them to concentrate on more intricate aspects of data quality and governance.

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Data-driven Digital Transformation Data Quality Optimization 98

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

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Data Quality Data Lake Data Warehouse Data-driven 63

DataKitchen

DECEMBER 7, 2023

Do you have data quality issues, a complex technical environment, and a lack of visibility into production systems? These challenges lead to poor quality analytics and frustrated end users. Getting your data reliable is a start, but many other problems arise even if your data could be better.

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Uncertainty Data Quality Dashboards Analytics 130

IBM Big Data Hub

MAY 9, 2024

At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data.

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Data Governance Data Quality Insurance Predictive Analytics 74

DataKitchen

APRIL 11, 2024

The goal is to reduce errors and operational overhead, allowing data teams to focus on delivering value. Statistical Process Control in Data Operations: Gil touched upon applying statistical process control techniques to data operations to monitor and control data quality and process performance.

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Statistics Manufacturing Data Processing Data Quality 152

IBM Big Data Hub

JANUARY 23, 2023

Simply put, data governance is the process of establishing policies, procedures, and standards for managing data within an organization. It involves defining roles and responsibilities, setting standards for data quality, and ensuring that data is being used in a way that is consistent with the organization’s goals and values.

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Data Governance Data Quality Management IT 73

TDAN

FEBRUARY 1, 2022

In this blog, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter the mundane, but necessary, task of data reconciliation. This is often a time-consuming and wasteful process.

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Data Warehouse Data Quality IT Data Governance 59

TDAN

MARCH 20, 2024

In the realm of big data, ensuring the reliability and accuracy of data is crucial for making well-informed decisions and actionable insights. Data cleansing, the process of detecting and correcting errors and inconsistencies in datasets, is critical to maintaining data quality.

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Big Data Data Quality Management 52