AWS Big Data

APRIL 3, 2024

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

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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.

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Data Quality Visualization Metadata Key Performance Indicator 109

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. In this post, we provide benchmark results of running increasingly complex data quality rulesets over a predefined test dataset.

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Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

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Visualization Cost-Benefit Big Data Prescriptive Analytics 145

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.

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AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

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AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

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CIO Business Intelligence

MAY 22, 2025

The process of collecting, processing and integrating data from various sources to ensure the digital twin mirrors the physical entity accurately. AI and machine learning models that analyze data and simulate scenarios to predict future behaviors and outcomes. Visualization. Ensure data quality.

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Enterprise Visualization Key Performance Indicator Machine Learning 112

AWS Big Data

MAY 23, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules assess the data based on fixed criteria reflecting current business states. We are excited to talk about how to use dynamic rules , a new capability of AWS Glue Data Quality.

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Data Quality Metrics Sales Data Lake 118

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 112

AWS Big Data

DECEMBER 4, 2024

Collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics with Amazon Q Developer , the most capable generative AI assistant for software development, helping you along the way. Having confidence in your data is key.

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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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DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

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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?

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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.

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Data Quality Data-driven Data Lake Metrics 98

DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. Ensuring that data is available, secure, correct, and fit for purpose is neither simple nor cheap.

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datapine

MAY 28, 2019

Maximum security and data privacy. Facing the challenges of poor data quality, dispersed through a number of spreadsheets and databases, this financial company was unable to track financial data in real-time and generate valuable insights needed to ensure their vendor payment, managed by the accounts payable department, is accurate and fast.

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Business Intelligence KPI Dashboards Reporting 317

datapine

JANUARY 21, 2020

The data-driven world doesn’t have to be overwhelming, and with the right BI tools , the entire process can be easily managed with a few clicks. One additional element to consider is visualizing data. This kind of report will become visual, easily accessed, and steadfast in gathering insights. Enhanced data quality.

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Business Intelligence Reporting Cost-Benefit Dashboards 259

Smarten

NOVEMBER 26, 2024

If the data is not easily gathered, managed and analyzed, it can overwhelm and complicate decision-makers. Data insight techniques provide a comprehensive set of tools, data analysis and quality assurance features to allow users to identify errors, enhance data quality, and boost productivity.’

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Machine Learning Data Quality Predictive Modeling Metadata 62

CIO Business Intelligence

FEBRUARY 6, 2025

They can also automate report generation and interpret data nuances that traditional methods might miss. Imagine generating complex narratives from data visualizations or using conversational BI tools that respond to your queries in real time. Tableau, Qlik and Power BI can handle interactive dashboards and visualizations.

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Unstructured Data Manufacturing Data Governance Sales 115

datapine

APRIL 16, 2019

But today, the development and democratization of business intelligence software empowers users without deep-rooted technical expertise to analyze as well as extract insights from their data. Data driven business decisions make or break companies. This is a testament to the importance of online data visualization in decision making.

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Smart Data Collective

FEBRUARY 23, 2021

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

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Big Data Visualization Data Quality Data-driven 142

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Now that we identified the data quality issues to address, we need to decide how to deal with each case.

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Visualization Cost-Benefit Data Quality Publishing 98

Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

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Data Quality Analytics Machine Learning Visualization 62

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

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Testing Data Quality Predictive Modeling Metrics 173

datapine

AUGUST 21, 2019

This gives to that sales graph an overall sense of visual contrast which makes it much more digestible at a glance. A perfect example of how to present sales data, this profit-boosting sales chart offers a panoramic snapshot of your agents’ overall upselling and cross-selling efforts based on revenue and performance.

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Sales Dashboards Visualization KPI 235

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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Data Quality Data Integration Metadata Cost-Benefit 63

David Menninger's Analyst Perspectives

OCTOBER 8, 2024

Collibra was founded in 2008 by Chief Executive Officer Felix Van de Maele and Chief Data Citizen Stijn Christiaens. Self-service access to data is only truly valuable if users can trust the data they have access to, however. Collibra also announced the acquisition of Husprey in 2023 for its SQL data notebook functionality.

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Data Quality Data Governance Enterprise Visualization 130

AWS Big Data

DECEMBER 4, 2024

Domain ownership recognizes that the teams generating the data have the deepest understanding of it and are therefore best suited to manage, govern, and share it effectively. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

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Metadata Data Governance Data Quality Data-driven 104

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. The data science and AI teams are able to explore and use new data sources as they become available through Amazon DataZone.

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IoT Machine Learning Metadata Data-driven 109

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

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Data Science Statistics Business Intelligence Visualization 214

datapine

DECEMBER 17, 2019

By understanding your core business goals and selecting the right key performance indicator ( KPI ) and metrics for your specific needs, you can use an information technology report sample to visualize your most valuable data at a glance, developing initiatives and making pivotal decisions swiftly and with confidence.

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CIO Business Intelligence

FEBRUARY 20, 2025

However, it is often unclear where the data needed for reporting is stored and what quality it is in. Often the data quality is insufficient to make reliable statements. Insufficient or incorrect data can even lead to wrong decisions, says Kastrati.

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Big Data Measurement Visualization Machine Learning 84

DataKitchen

MAY 10, 2021

A robust process checks source data and work-in-progress at each processing step along the way to polished visualizations, charts, and graphs. Figure 1: The process of transforming raw data into actionable business intelligence is a manufacturing process. It’s not about data quality . It’s not only about the data.

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Testing Manufacturing Data Quality Statistics 214

Rocket-Powered Data Science

MARCH 20, 2023

Content includes reports, documents, articles, presentations, visualizations, video, and audio representations of the insights and knowledge that have been extracted from data. We could further refine our opening statement to say that our business users are too often in a state of being data-rich, but insights-poor, and content-hungry.

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Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

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Visualization Reporting Metadata Enterprise 98

Smarten

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! If you want to create an environment with a culture and processes that are balanced to accommodate data agility and data quality, you can start here: Benefits of Augmented Analytics Balance.

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