AWS Big Data

MARCH 26, 2024

In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360. The following figure shows some of the metrics derived from the study. Data warehouses can provide a unified, consistent view of a vast amount of customer data for C360 use cases.

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

Alation

JULY 19, 2022

Modern data catalogs also facilitate data quality checks. Historically restricted to the purview of data engineers, data quality information is essential for all user groups to see. Data scientists often have different requirements for a data catalog than data analysts.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Wayne Yaddow

FEBRUARY 26, 2025

If your source data structure changes or new business logic is added, the process AI can create corresponding tests on the fly, reducing the maintenance burden on your QA team. This leads to faster iteration cycles and helps maintain high data quality standards, even as data pipelines grow morecomplex.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Data-driven 52

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. This means establishing and enforcing policies and processes, standards, roles, and metrics. Why Is Data Governance in Healthcare Important? Healthcare data is valuable and sensitive, so it must be protected.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? There are essentially four types encountered: image/video, audio, text, and structured data. If you’re currently wrangling with data quality issues, you might start looking ahead at how staffing or legal concerns will be among the next hurdles to confront.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

AWS Big Data

JULY 12, 2023

A comprehensive testing framework ensures that your models consistently deliver accurate and reliable data, while modularity enables faster development via component reusability. Combined, these features can improve your data team’s velocity, ensure higher data quality, and empower team members to assume ownership.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

O'Reilly on Data

APRIL 19, 2021

The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%). Bad data yields bad results at scale. form data).

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Jet Global

MAY 9, 2024

Monitoring can include tracking performance metrics such as execution time and resource usage, and logging errors or failures for troubleshooting and remediation. It also includes data validation and quality checks to ensure the accuracy and integrity of the data being processed. How is ELT different from ETL?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

DECEMBER 17, 2024

Prevent the inclusion of invalid values in categorical data and process data without any data loss. Conduct data quality tests on anonymized data in compliance with data policies Conduct data quality tests to quickly identify and address data quality issues, maintaining high-quality data at all times.

Data Quality 94

Data Quality Testing Metrics Optimization 94

CIO Business Intelligence

APRIL 1, 2025

In CIOs 2024 Security Priorities study, 40% of tech leaders said one of their key priorities is strengthening the protection of confidential data. Error-filled, incomplete or junk data can make costly analytics efforts unusable for organizations. Ravinder Arora elucidates the process to render data legible.

Data-driven 59

Data-driven Data Quality Data Governance Business Objectives 59

Anmut

APRIL 14, 2025

Condition Visibility : Physical assets can be inspected visually or measured using predefined metrics. Missing context, ambiguity in business requirements, and a lack of accessibility makes tackling data issues complex. Get in touch to learn how we can help you maximise the value of your data.

Uncertainty 52

Uncertainty Data Quality Business Objectives Measurement 52

BI-Survey

FEBRUARY 27, 2025

Advanced: Does it leverage AI/ML to enrich metadata by automatically linking glossary entries with data assets and performing semantic tagging? Leading-edge: Does it provide data quality or anomaly detection features to enrich metadata with quality metrics and insights, proactively identifying potential issues?

Unstructured Data 52

Unstructured Data Metadata Data Quality Data Governance 52

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. This comparison will help guide you in making informed decisions on enhancing your data lake environments.

Data Lake 98

Data Lake IoT Metadata Testing 98

AWS Big Data

FEBRUARY 25, 2025

If data mapping has been enabled within the data processing job, then the structured data is prepared based on the given schema. This output is passed to next phase where data transformations and business validations can be applied. After this step, data is loaded to specified target.

Data Processing 58

Data Processing Machine Learning Data-driven Cost-Benefit 58

CIO Business Intelligence

APRIL 16, 2025

But what kind of data do you need for a solid use case? We used to need structured data because our machine learning models expected field-level information. Today, we dont care if the data is structured because we can ingest it all, whether images, recordings, documents, PDF files, or large data lakes.

ROI 71

ROI Measurement Testing Data Lake 71