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 111

Data Quality Visualization Metadata Key Performance Indicator 111

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.

Data Quality 98

Data Quality Statistics Data Lake Visualization 98

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

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities.

Testing 300

Testing Machine Learning Consulting Data Science 300

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

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.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

Octopai

MARCH 23, 2022

Assuming all checked out, you’d definitely feel comfortable eating that meat. Data lineage tools give you exactly that kind of transparent, x-ray vision into your data quality. Data Supervision. Having the right data intelligence tools can be a make-or-break for data responsibility success.

Data Quality 98

Data Quality Reporting Modeling Interactive 98

CIO Business Intelligence

AUGUST 2, 2022

The second is the data quality in our legacy systems. So, as we implement new solutions, we are looking at the data quality component and really thinking through why it matters to collect certain data in some categories and making sure that solutions are part of that new implementation. That’s one.

Data Quality 97

Data Quality Digital Transformation Machine Learning Predictive Analytics 97

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.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

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. Data programming.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

O'Reilly on Data

MARCH 18, 2020

By contrast, AI adopters are about one-third more likely to cite problems with missing or inconsistent data. The logic in this case partakes of garbage-in, garbage out : data scientists and ML engineers need quality data to train their models. This is consistent with the results of our data quality survey.

Enterprise 349

Enterprise Deep Learning Data Governance Risk 349

DataKitchen

JANUARY 25, 2022

Ensuring that data is available, secure, correct, and fit for purpose is neither simple nor cheap. Companies end up paying outside consultants enormous fees while still having to suffer the effects of poor data quality and lengthy cycle time. . When a job is automated, there is little advantage to outsourcing. .

Consulting 244

Consulting Testing Data Lake Data Quality 244

O'Reilly on Data

MARCH 24, 2020

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. This definition of low-quality data defines quality as a function of how much work is required to get the data into an analysis-ready form.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

Jim Harris

JANUARY 1, 2016

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. In order for you to make sense of those data elements, you require business context.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

CIO Business Intelligence

FEBRUARY 26, 2025

Its a definite challenge, Avancini says. If they want to make certain decisions faster, we will build agents in line with their risk tolerance. D&B is not alone in worrying about the risks of AI agents. And with legacy systems in particular, this kind of fine-grained access control might be difficult, he adds.

IT 141

IT Enterprise Interactive Data Quality 141

Cloudera

NOVEMBER 13, 2024

In today’s heterogeneous data ecosystems, integrating and analyzing data from multiple sources presents several obstacles: data often exists in various formats, with inconsistencies in definitions, structures, and quality standards.

Metadata 90

Metadata Management Data Governance Data-driven 90

CIO Business Intelligence

NOVEMBER 13, 2024

There’s already more low-quality AI content flooding search results, and this can hurt employees looking for information both on the public web and in enterprise knowledge repositories. The information volume piece is definitely one of the areas where productivity could go down,” says Woolley.

IT 141

IT Consulting ROI Cost-Benefit 141

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.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

O'Reilly on Data

OCTOBER 13, 2020

This distinction assumes a slightly different definition of debugging than is often used in software development. It is entirely possible for an AI product’s output to be absolutely correct from the perspective of accuracy and data quality, but too slow to be even remotely useful.

Management 314

Management Machine Learning Metrics Modeling 314

Rocket-Powered Data Science

FEBRUARY 15, 2023

A business-disruptive ChatGPT implementation definitely fits into this category: focus first on the MVP or MLP. Clean it, annotate it, catalog it, and bring it into the data family (connect the dots and see what happens). When people are encouraged to experiment, where small failures are acceptable (i.e.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

OCTOBER 23, 2024

Data literacy across the company was a challenge because, as is often the case, we were all describing our business data a little differently. Early on, we ground through creating our first data catalog, building clearer definitions of our target attributes and metrics.

Enterprise 119

Enterprise Dashboards KPI Data Lake 119

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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. What growth targets has the company set?

Big Data 84

Big Data Measurement Visualization Machine Learning 84

datapine

JANUARY 21, 2020

Enhanced data quality. One of the most clear-cut and powerful benefits of data intelligence for business is the fact that it empowers the user to squeeze every last drop of value from their data. With so much information and such little time, intelligent data analytics can seem like an impossible feat.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

Anmut

JULY 12, 2021

Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem. In this blog post, we’ll compare traditional data quality vs data condition — the big picture approach to data improvement we use here at Anmut.

Data Quality 52

Data Quality Measurement Metrics Dashboards 52

TDAN

JUNE 18, 2019

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Governance 90

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

CIO Business Intelligence

JULY 18, 2022

The true value of a strong data supply chain is improved data quality, but leaders might miss the need to communicate that broadly across the organization. We are exposed to data and processes needed to gather, cleanse, and analyze information, and we tend to project our understanding of that to others in the organization.

Data Quality 105

Data Quality Metrics Measurement Cost-Benefit 105

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. The introduction of generative AI (genAI) and the rise of natural language data analytics will exacerbate this problem.

Management 111

Management Data Governance Data Science Reporting 111

DataKitchen

MAY 10, 2021

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214

Testing Manufacturing Data Quality Statistics 214

DataKitchen

MARCH 12, 2024

Director, Data Analytics Team “We had some data issues. Thanks to Observability, I could diagnose the problem – definitely helped me a lot during the process.” It’s definitive, and that changes the game, especially for senior leadership.” That was amazing for the team.” Databricks was all green.

Metrics 117

Metrics Software Cost-Benefit Testing 117

Ontotext

NOVEMBER 9, 2023

While everyone may subscribe to the same design decisions and agree on an ontology, there may be differences in the data quality. In such situations, data must be validated. The post SHACL-ing the Data Quality Dragon I: the Problem and the Tools appeared first on Ontotext. Sometimes there is no room for error.

Data Quality 64

Data Quality Testing Reporting Metadata 64

Smart Data Collective

APRIL 5, 2022

Drones Surveyors Are Pioneers in the Data Analytics Field. While this is definitely true, there are a few best practices that users need to learn to use it properly. Drone surveyors must also know how to gather and use data properly. They will need to be aware of the potential that data can bring to entities using drones.

Data Collection 128

Data Collection Data Quality Big Data Data-driven 128

Alation

SEPTEMBER 28, 2022

In essence, DataOps is a practice that helps organizations manage and govern data more effectively. However, there is a lot more to know about DataOps, as it has its own definition, principles, benefits, and applications in real-life companies today – which we will cover in this article! Automated testing to ensure data quality.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. When can you declare it done?

Testing 152

Testing Metadata Dashboards Statistics 152

CIO Business Intelligence

MARCH 19, 2025

Were a long ways from that but because of the complexity of data residency of some larger fortune 500 companies, and theyre definitely thinking about true costs in the cloud and more control, he says. Wise also discussed data quality, and the cultural shift to deliver and continuously improve on technology excellence.

B2B 64

B2B Cost-Benefit Data Quality Sales 64

datapine

AUGUST 7, 2019

Exclusive Bonus Content: Your Definitive Guide to SaaS & Dashboards! Whether you need to develop an IT report or tackle deeper into the financial analytics side of the business, a dashboard will prove its worth when you see all your data in a clean, interactive screen. 1) Data management. Let’s get started. 2) Vision.

Dashboards 168

Dashboards Management KPI Cost-Benefit 168