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

datapine

DECEMBER 17, 2019

As in many other industries, the information technology sector faces the age-old issue of producing IT reports that boost success by helping to maximize value from a tidal wave of digital data. Get our summary to learn the key elements and benefits of IT reporting! What Are IT Reports? Why Do You Need An IT Report?

Reporting 173

Reporting IT Key Performance Indicator Dashboards 173

Jet Global

MARCH 4, 2020

A manufacturing Key Performance Indicator (KPI) or metric is a well defined and quantifiable measure that the manufacturing industry uses to gauge its performance over time. The only way to stay ahead in this fiercely competitive industry is through the implementation of manufacturing KPIs and metrics. What Is A Manufacturing KPI?

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Testing 124

Testing Metrics Data Quality Dashboards 124

Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

Data Quality 79

Data Quality Strategy Business Objectives Sales 79

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

Data Quality 52

Data Quality Metadata Reporting Metrics 52

Alation

DECEMBER 7, 2021

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it. trillion each year due to poor data quality.

Data Quality 52

Data Quality Data-driven Metrics Dashboards 52

Andrew White

APRIL 5, 2019

An oft heard inquiry from clients is, “What is the right metric to use?” The context might be for: Defining data quality. Reporting the business impact of a data governance initiative. Monitoring the progress of a digital or data-driven transformation. A simple example exposed the potential value of PM.

Metrics 80

Metrics Key Performance Indicator KPI Marketing 80

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

Data Quality 52

Data Quality IT Data Governance Sales 52

Jet Global

MAY 8, 2024

Logi Symphony harnesses the strengths of two recent insightsoftware acquisitions, Logi Analytics and Dundas BI, to enable software teams to rapidly design, build, and embed interactive dashboards, pixel-perfect reports and data visualizations with fast connectivity and access to modern data infrastructure.

Business Intelligence 52

Business Intelligence Reporting Measurement Software 52

IBM Big Data Hub

JULY 25, 2023

Independent research firm Verdantix recently identified IBM as a leader in their report, “ Green Quadrant: ESG Reporting and Data Management Software ” (July 17, 2023), which evaluated and provided a detailed assessment of solution providers and their product offerings.

Software 57

Software Reporting Management Data Quality 57

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’ (..)

Testing 117

Testing Data-driven Metrics Data Quality 117

CIO Business Intelligence

APRIL 25, 2024

So the social media giant launched a generative AI journey and is now reporting the results of its experience leveraging Microsoft’s Azure OpenAI Service. Without automated evaluation, LinkedIn reports that “engineers are left eye-balling results and testing on a limited set of examples and having a more than a 1+ day delay to know metrics.”

IT 131

IT Experimentation Cost-Benefit Metrics 131

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 361

Marketing Experimentation Metrics Testing 361

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? A data profiling tool can help you by automating some of the grunt work needed to begin your analysis. You, Data-Dude, takin’ on the defects. Data Cleansing.

Data Quality 56

Data Quality Enterprise Business Intelligence Data Governance 56

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. SPC tests can do the same thing for the data flowing through your pipelines.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

JULY 18, 2022

While this may seem like an odd question, understanding organizational change levers can help uncover opportunities for improving your data supply-chain processes. A key challenge with organizational alignment is communicating across all departments the goals, metrics, and benefits of a process or function.

Data Quality 91

Data Quality Metrics Measurement Cost-Benefit 91

CIO Business Intelligence

MAY 2, 2023

And while KPMG reports that 72% of CEOs have aggressive digital investment strategies, McKinsey details a harsh reality that 70% of transformations fail. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality.

Digital Transformation 129

Digital Transformation IT Data-driven Metrics 129

CIO Business Intelligence

JUNE 23, 2022

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. First mile/last mile impacts.

Data Quality 91

Data Quality Key Performance Indicator Metrics KPI 91

DataKitchen

JUNE 19, 2023

” – Gautama Buddha When your data team is in crisis from errors in production, complaining customers, and uncaring data providers, we all wish we could be unshaken as the Buddha. Our recent survey showed that 97% of data engineers report experiencing burnout in their day-to-day jobs. Donkey: Oh, they have layers.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Jet Global

OCTOBER 27, 2020

It provides high value relative to the time and resources invested, it benefits every area of the organization, and given the right reporting tools, it is easy to put in place. What Is Exception Reporting? For example, an exception report might list all budget categories in which expenses exceeded the budgeted amount by more than 5%.

Reporting 52

Reporting Data Quality Cost-Benefit Sales 52

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

Jet Global

OCTOBER 26, 2023

Reporting teams need to go beyond native reporting with deeper, flexible analysis of their data. Without the right control, they struggle with inflexible report layouts and spend days dumping data into spreadsheets, limiting the available time to focus on value-added analysis.

Data Quality 52

Data Quality Reporting Operational Reporting Finance 52

CIO Business Intelligence

DECEMBER 21, 2022

The team also developed an enterprise-wide system for tracking ESG metrics, like Scope 1 and 2 GHG emissions. Insights from that system are highlighted regularly in the company’s sustainability reports. Focus on data governance Data governance is vital to ESG initiatives.

Metrics 98

Metrics Data Governance Reporting Dashboards 98

InsightOut

FEBRUARY 2, 2024

This is where InsightOut steps in, offering e-commerce companies the tools they need to clean, analyze, and report on key data metrics. Let's explore how InsightOut is leading the way and revolutionizing the way e-commerce businesses leverage data. Pristine Data Cleansing For e-commerce, data quality is non-negotiable.

Key Performance Indicator 40

Key Performance Indicator Metrics Dashboards Reporting 40

CIO Business Intelligence

APRIL 8, 2024

Jamie Capel-Davies, head of science and technical for ITF, says metrics don’t mean much if you can’t communicate them effectively in time to make use of them. One of the key things we were looking at was what were the most important metrics and how can they be communicated effectively,” he says.

Analytics 91

Analytics Broadcasting Predictive Analytics Metrics 91

DataKitchen

OCTOBER 11, 2021

The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. All the code, Talend job, and the BI report are version controlled using Git. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes.

Testing 152

Testing Metadata Dashboards Statistics 152

Juice Analytics

APRIL 6, 2021

At Juice, we are working everyday to create these habits and we wanted to share how we are building a data-first mindset and where we look for inspiration. Habit 1: Define shared metrics Data fluency requires getting everyone on the same page as to what matters most.

Metrics 119

Metrics Dashboards Data-driven Data Quality 119

DataKitchen

NOVEMBER 18, 2022

So, the only way for a data journey to truly observe what’s happening is to get his tools and pipelines to auto-report events. An effective DataOps observability solution requires supporting infrastructure for the journeys to observe and report what’s happening across your data estate. Setting Expectations.

Testing 130

Testing Statistics Measurement Metrics 130

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. 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. It’s not about data quality

Testing 214

Testing Manufacturing Data Quality Statistics 214

Alation

FEBRUARY 14, 2023

From rebranding data governance in your organization to demonstrating real business impacts, there’s a lot you can do to bring everyone in your business on board. The role of monitoring, measuring, and metrics So, you’ve got the first step done; you’ve implemented data governance and everyone in your organization is on board.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Alation

OCTOBER 5, 2021

Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols. Why is your data governance strategy failing? They may simply move and copy data without going through all of the necessary protocols related to data security and other best-practice standards.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. Athena exposes the content of the reporting zone for consumption.

Optimization 92

Optimization B2B Data Quality Sales 92

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). These reports include the cash flow statement, income statement, and balance sheet.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

O'Reilly on Data

OCTOBER 13, 2020

To support verification in these areas, a product manager must first ensure that the AI system is capable of reporting back to the product team about its performance and usefulness over time. Continuous retraining : a data-driven approach that employs constant monitoring of the model’s key performance indicators and data quality thresholds.

Management 240

Management Metrics Machine Learning Modeling 240

CIO Business Intelligence

JANUARY 20, 2023

According to a recent IDC whitepaper , leaders saw on average two and a half times better results than other organizations in many business metrics. All of a sudden, you’re trying to give this data to somebody who’s not a data person,” he says, “and it’s really easy for them to draw erroneous or misleading insights from that data.”

Data Lake 120

Data Lake Data-driven Finance Data Architecture 120