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

Andrew White

AUGUST 26, 2020

I spoke to a client recently who had this question: “I need help to develop a survey to ask our employees around the company how they regard the various subjective metrics tied to data quality.” I went on: What if the subjective measures all get scored or rated at 100%? ” The question got more curious.

Data Quality 52

Data Quality Data Governance Metrics Measurement 52

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

datapine

AUGUST 7, 2019

Exclusive Bonus Content: Your Definitive Guide to SaaS & Dashboards! A SaaS dashboard consolidates and visualizes critical SaaS metrics, covering sales, marketing, finance, consumer support, management, and development to offer an unobstructed panoramic view of the SaaS business and achieve better business performance and profit.

Dashboards 168

Dashboards Management KPI Cost-Benefit 168

CIO Business Intelligence

NOVEMBER 13, 2023

Reimagination of business processes sits at the core of digital transformation, and so, by definition, digital transformation challenges the status quo, throwing we-have-always-done-it-this-way sentiment out of the window. Ensuring data quality, privacy, and security is essential.

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing? Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

Alation

AUGUST 17, 2022

“This failure is often the difference between successful implementations and data breaches. If your definitions are bad, so is your governance/risk/security. At the same time, data governance leaders must deliver tangible business value. It comes down to the question: What is the value of your data? ” Parting Words.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

CDW Research Hub

MAY 29, 2019

Start meeting, strategizing, and creating the justification for data governance. Agree on a definition of data governance for organization. Identify where your company currently stands in data governance, while keeping in mind your master data management plan, data quality goals, data stewardship, data lineage, and metadata.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

Occam's Razor

AUGUST 22, 2011

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. Key To Your Digital Success: Web Analytics Measurement Model. Be data driven?" " Measuring Incrementality: Controlled Experiments to the Rescue! Barriers To An Effective Web Measurement Strategy [+ Solutions!].

KPI 124

KPI Metrics Measurement ROI 124

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

datapine

AUGUST 21, 2019

A definitive sales graph example for any growing organization. By exploring these metrics periodically, you’ll be able to drill down into elements including commissions and bonuses, performance consistency, and areas that need improvement, gaining the ability to allocate your support as well as resources more efficiently as a result.

Sales 235

Sales Dashboards KPI Visualization 235

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. How do we think about the quality of human ratings, and how do we quantify our understanding is the subject of this post. While human-labeled data is critical to many important applications, it also brings many challenges.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 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 105

Data Quality Metrics Measurement Cost-Benefit 105

O'Reilly on Data

OCTOBER 13, 2020

This distinction assumes a slightly different definition of debugging than is often used in software development. Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics.

Management 246

Management Metrics Machine Learning Modeling 246

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

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 Quality 300

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

datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Every serious business uses key performance indicators to measure and evaluate success. Enhanced data quality. It doesn’t stop here. Operational optimization and forecasting.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? Let’s start however with some definitions. A number of factors can play into the accuracy of data capture. Timing issues with Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

FineReport

MAY 25, 2023

An HR dashboard functions as an advanced analytics tool that utilizes interactive data visualizations to present crucial HR metrics. Similar to various other business departments, human resources is gradually transforming into a data-centric function. Otherwise, it may become a ‘vanity metric’ in the HR dashboard.

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

Occam's Razor

JUNE 8, 2006

I am often asked what we look for when we hire Web Analysts or what quality do good Analysts possess or how to measure if a resource that already exists is optimal or how to mentor / motivate / guide our more junior Analysts to propel them to become great Analysts. We all agree that reporting is not analysis. Mostly we react.

KPI 94

KPI Measurement Statistics Metrics 94

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

APRIL 21, 2014

I am having issues prioritizing 1) recommending fixing on site issues affecting real traffic levels versus 2) correcting significant configuration issues in Analytics measuring current site traffic. Even the worst analytics configuration in the world will most likely allow you to measure cart and checkout abandonment rate.

Marketing Analytics 131

Marketing Analytics Marketing Analytics Measurement 131

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. What's possible to measure. What's not possible to measure.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

datapine

APRIL 15, 2020

That said, in this article, we will go through both agile analytics and BI starting from basic definitions, and continuing with methodologies, tips, and tricks to help you implement these processes and give you a clear overview of how to use them.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. This is a key component of active data governance.

Metadata 52

Metadata IT Metrics Data-driven 52

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. In other words, D&A plays a key role in the foundational measuring angle. This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. They can all help you at any time depending not the context.

Analytics 64

Analytics Measurement Modeling Data-driven 64

datapine

AUGUST 29, 2022

Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage. With that in mind, we have prepared a list of the top 19 definitive data analytics and big data books, along with magazines and authentic readers’ reviews upvoted by the Goodreads community. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration. Brace yourselves for impact.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

datapine

FEBRUARY 22, 2022

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. A planned BI strategy will point your business in the right direction to meet its goals by making strategic decisions based on real-time data. It’s that simple.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

DataKitchen

APRIL 26, 2021

At Workiva, they recognized that they are only as good as their data, so they centered their initial DataOps efforts around lowering errors. Hodges commented, “Our first focus was to up our game around data quality and lowering errors in production. Multiple Metrics for Success. At GSK, success is all about adoption.

Measurement 246

Measurement Metrics Data-driven Testing 246

DataKitchen

JUNE 24, 2021

GE formed its Digital League to create a data culture. One of the keys for our success was really focusing that effort on what our key business initiatives were and what sorts of metrics mattered most to our customers. So we really prioritized the data that we thought had the biggest chance of delivering success in the end.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

MARCH 5, 2021

It includes the processes, roles and policies, standards and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.”. Organizations have much to gain from learning about and implementing a data governance framework. Data Governance Roles. Democratizing Data.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

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

AWS Big Data

AUGUST 14, 2023

When are data products deprecated, and who is accountable for the consequences to their consumers? How do we define “risk” and “value” in the context of data products, and how can we measure this? Whose responsibility is it to justify the existence of a given data product?

Management 81

Management Risk Measurement Optimization 81