Analytics Vidhya

NOVEMBER 8, 2023

In the data-driven world […] The post Monitoring Data Quality for Your Big Data Pipelines Made Easy appeared first on Analytics Vidhya. Determine success by the precision of your charts, the equipment’s dependability, and your crew’s expertise. A single mistake, glitch, or slip-up could endanger the trip.

Data Quality 341

Data Quality Big Data Data-driven Analytics 341

Analytics Vidhya

SEPTEMBER 23, 2024

Introduction Ensuring data quality is paramount for businesses relying on data-driven decision-making. As data volumes grow and sources diversify, manual quality checks become increasingly impractical and error-prone.

Data Quality 271

Data Quality Data-driven Data Integration Analytics 271

DataKitchen

APRIL 24, 2025

White Paper: A New, More Effective Approach To Data Quality Assessments Data quality leaders must rethink their role. They are neither compliance officers nor gatekeepers of platonic data ideals. In this new approach, the data quality assessment becomes a tool of persuasion and influence.

Data Quality 100

Data Quality Metrics IT 100

DataKitchen

APRIL 18, 2025

Welcome to the Data Quality Coffee Series with Uncle Chip Pull up a chair, pour yourself a fresh cup, and get ready to talk shopbecause its time for Data Quality Coffee with Uncle Chip. This video series is where decades of data experience meet real-world challenges, a dash of humor, and zero fluff.

Data Quality 100

Data Quality Dashboards Testing IT 100

Corinium

JANUARY 13, 2020

In the last decade regulatory requirements in financial services increased significantly.

Data Quality 311

Data Quality Analytics 311

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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Data Quality Metrics Data-driven Management 241

DataKitchen

OCTOBER 19, 2021

The post Data Quality: Volume, interdependencies can create big problems first appeared on DataKitchen.

Data Quality 246

Data Quality 246

DataKitchen

MAY 14, 2024

Data Observability and Data Quality Testing Certification Series We are excited to invite you to a free four-part webinar series that will elevate your understanding and skills in Data Observation and Data Quality Testing. Slides and recordings will be provided.

Data Quality 195

Data Quality Testing Metrics Measurement 195

DataKitchen

SEPTEMBER 18, 2024

A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. 73% of data practitioners do not trust their data (IDC).

Scorecard 177

Scorecard Data Quality Measurement Testing 177

DataKitchen

APRIL 18, 2025

Welcome to the Data Quality Coffee Series with Uncle Chip Pull up a chair, pour yourself a fresh cup, and get ready to talk shopbecause its time for Data Quality Coffee with Uncle Chip. This video series is where decades of data experience meet real-world challenges, a dash of humor, and zero fluff.

Data Quality 130

Data Quality Dashboards Testing IT 130

Corinium

FEBRUARY 3, 2020

Using data to inform business decisions only works when the data is correct. Unfortunately for the insurance industry’s data leaders, many data sources are riddled with inaccuracies. Data is the lifeblood of the insurance industry.

Insurance 221

Insurance Data Quality Risk Management 221

Anmut

JANUARY 30, 2025

They made us realise that building systems, processes and procedures to ensure quality is built in at the outset is far more cost effective than correcting mistakes once made. How about data quality? Redman and David Sammon, propose an interesting (and simple) exercise to measure data quality.

Data Quality 52

Data Quality Cost-Benefit Statistics Data-driven 52

DataKitchen

MARCH 20, 2025

We’ve identified two distinct types of data teams: process-centric and data-centric. Understanding this framework offers valuable insights into team efficiency, operational excellence, and data quality. Process-centric data teams focus their energies predominantly on orchestrating and automating workflows.

Data Quality 161

Data Quality Testing Metrics Management 161

DataKitchen

AUGUST 6, 2024

DataKitchen’s Data Quality TestGen found 18 potential data quality issues in a few minutes (including install time) on data.boston.gov building permit data! Imagine a free tool that you can point at any dataset and find actionable data quality issues immediately! first appeared on DataKitchen.

Data Quality 124

Data Quality Testing Cost-Benefit Software 124

KDnuggets

JANUARY 2, 2025

Want to run some quick data quality checks? Here are 10 pandas one-liners that'll come in handy.

Data Quality 135

Data Quality 135

CIO Business Intelligence

DECEMBER 12, 2024

Confidence from business leaders is often focused on the AI models or algorithms, Erolin adds, not the messy groundwork like data quality, integration, or even legacy systems. Data quality is a problem that is going to limit the usefulness of AI technologies for the foreseeable future, Brown adds.

IT 134

IT Data Quality Experimentation Machine Learning 134

CIO Business Intelligence

APRIL 8, 2025

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

DECEMBER 9, 2024

data engineers delivered over 100 lines of code and 1.5 data quality tests every day to support a cast of analysts and customers. The team used DataKitchen’s DataOps Automation Software, which provided one place to collaborate and orchestrate source code, data quality, and deliver features into production.

Data Quality 161

Data Quality Data Lake Testing Statistics 161

AWS Big Data

AUGUST 8, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules commonly assess the data based on fixed criteria reflecting the current business state. In this post, we demonstrate how this feature works with an example.

Data Quality 113

Data Quality Statistics Visualization Metrics 113

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

To improve data reliability, enterprises were largely dependent on data-quality tools that required manual effort by data engineers, data architects, data scientists and data analysts.  With the aim of rectifying that situation, Bigeye’s founders set out to build a business around data observability.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

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

DECEMBER 4, 2024

We have lots of data conferences here. I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? Over the years, I’ve seen a trend — more and more emphasis on AI. This is my version of […]

Unstructured Data 52

Unstructured Data Data Quality Data Architecture Modeling 52

DataKitchen

JULY 12, 2023

The Syntax, Semantics, and Pragmatics Gap in Data Quality Validate Testing Data Teams often have too many things on their ‘to-do’ list. Each unit will have unique data sets with specific data quality test requirements. One of the standout features of DataOps TestGen is the power to auto-generate data tests.

Data Quality 130

Data Quality Testing Manufacturing Finance 130

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Ensuring Data Quality in New Data Sources (#1) Introduction to Data Evaluation in Data Observability Ensuring their quality and integrity before incorporating new data sources into production is paramount.

Data Quality 124

Data Quality Interactive Dashboards Testing 124

AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

Data Quality 107

Data Quality Visualization Metadata Key Performance Indicator 107

Analytics Vidhya

MAY 30, 2023

Introduction In the realm of machine learning, the veracity of data holds utmost significance in the triumph of models. Inadequate data quality can give rise to erroneous predictions, unreliable insights, and overall performance.

Machine Learning 325

Machine Learning Data Quality Modeling Analytics 325

KDnuggets

JANUARY 8, 2025

This article shows how to use Great Expectations to check data quality in data science projects.

Data Quality 108

Data Quality Data Science 108

Analytics Vidhya

SEPTEMBER 2, 2021

This article was published as a part of the Data Science Blogathon Overview Running data projects takes a lot of time. Poor data results in poor judgments. Running unit tests in data science and data engineering projects assures data quality. You know your code does what you want it to do.

Testing 342

Testing Data Quality Data-driven Data Science 342

AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

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Data Quality Data Lake Data Warehouse Metrics 96