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. Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

CIO Business Intelligence

JANUARY 20, 2023

Truly data-driven companies see significantly better business outcomes than those that aren’t. According to a recent IDC whitepaper , leaders saw on average two and a half times better results than other organizations in many business metrics. This is called data democratization. Security and compliance risks also loom. “All

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

BizAcuity

NOVEMBER 13, 2024

Business intelligence consulting services offer expertise and guidance to help organizations harness data effectively. Beyond mere data collection, BI consulting helps businesses create a cohesive data strategy that aligns with organizational goals.

Consulting 52

Consulting Data-driven Cost-Benefit Business Intelligence 52

CIO Business Intelligence

NOVEMBER 22, 2022

Data observability becomes business-critical Data observability extends the concept of data quality by closely monitoring data as it flows in and out of the applications. CIOs should first understand the different approaches to observing data and how it differs from quality management,” he notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

APRIL 29, 2022

In this new era the role of humans in the development process also changes as they morph from being software programmers to becoming ‘data producers’ and ‘data curators’ – tasked with ensuring the quality of the input. Further, data management activities don’t end once the AI model has been developed.

Data Governance 145

Data Governance IT Data Lake Risk 145

datapine

JANUARY 31, 2022

As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”. A great way to illustrate the operational benefits of business intelligence.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

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. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

datapine

FEBRUARY 22, 2022

Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Clean data in, clean analytics out.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. Database design is often an important part of the business analyst role.

Statistics 97

Statistics Metrics Visualization Finance 97

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

IBM Big Data Hub

SEPTEMBER 11, 2023

A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 85

Data-driven IT Measurement Cost-Benefit 85

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. How Alation Activates Data Governance.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Alation

NOVEMBER 11, 2021

Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance? Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

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. Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

FineReport

MAY 31, 2023

Financial Performance Dashboard The financial performance dashboard provides a comprehensive overview of key metrics related to your balance sheet, shedding light on the efficiency of your capital expenditure. While sales dashboards focus on future prospects, accounting primarily focuses on analyzing the same metrics retrospectively.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Alation

OCTOBER 12, 2021

Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Yet the explosion of data collection and volume presents new challenges. The third challenge was around trusting the data. The fourth challenge was around using the data. Set consistent data policies.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Data lineage features.

Metadata 64

Metadata Data Governance Dashboards Software 64

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. What metrics are used to evaluate success?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

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 364

Marketing Experimentation Metrics Testing 364

Andrew White

JANUARY 9, 2022

This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. Check this out: The Foundation of an Effective Data and Analytics Operating Model — Presentation Materials. Much as the analytics world shifted to augmented analytics, the same is happening in data management.

Analytics 64

Analytics Measurement Data-driven Modeling 64

Occam's Razor

APRIL 21, 2014

The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. We wonder why data people are not loved. :). I believe these two posts with a collection of some of my favorite metrics will inspire you: 1.

Marketing Analytics 132

Marketing Analytics Marketing Analytics Metrics 132

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff! All that is great. For most of us, you plus the CMO/equivalent.].

Analytics 142

Analytics Data-driven Strategy Consulting 142

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. Last, we’ll provide a case study of how xRR can be used to measure improvements in a data-labeling platform.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. You know, typically, when you think about running projects, running teams, in terms of setting the priorities for projects, in terms of describing, what are the key metrics for success for a project, that usually falls on product management.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

FEBRUARY 4, 2019

These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

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

Jet Global

MARCH 4, 2024

Moving data across siloed systems is time-consuming and prone to errors, hurting data quality and reliability. Built on proven technology trusted by thousands, it delivers investor-grade data with robust controls, audit trails, and security. Need quarterly reporting with in-depth metrics?

Reporting 52

Reporting Data-driven Metrics Software 52

CIO Business Intelligence

NOVEMBER 11, 2024

Liberating siloed data (SCADA, sensors, manual, satellite apps) and aggregating it with structured (ERP) data, and then creating a 360-degree view on almost anything – that is our holy grail. How do you ensure that your data collection systems for sustainability reports are robust, and data is clean and standardized?

Reporting 96

Reporting IoT Data Collection Data Quality 96

CIO Business Intelligence

FEBRUARY 5, 2025

By focusing on domains where data quality is sufficient and success metrics are clear such as increased conversion rates, reduced downtime, or improved operational efficiency companies can more easily quantify the value AI brings. Are the KPIs aligned with measurable business outcomes that stakeholders can rally behind?

Cost-Benefit 117

Cost-Benefit ROI Metrics Measurement 117

CIO Business Intelligence

APRIL 1, 2025

Our data governance frameworks define clear standards for data quality, accuracy, and relevance to collect usable data that drives meaningful insights. We also leverage automated data classification, role-based access controls (RBAC) and regular audits ensure only high-quality data is stored and analyzed.

Data-driven 59

Data-driven Data Quality Data Governance Business Objectives 59

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage does not directly improve data quality.

Testing 130

Testing Data Governance Data Quality Data-driven 130

CIO Business Intelligence

MAY 8, 2025

One is a public repository such as Common Crawl, which is a free, open-source storehouse of historical and current web crawl data available to pretty much anyone on the internet. Maintain detailed and transparent records of data sources, collection methods, and preprocessing techniques.

Modeling 85

Modeling Cost-Benefit Data Collection Predictive Analytics 85