O'Reilly on Data

JUNE 19, 2019

A catalog or a database that lists models, including when they were tested, trained, and deployed. A catalog of validation data sets and the accuracy measurements of stored models. Versioning (of models, feature vectors , data) and the ability to roll out, roll back, or have multiple live versions.

Modeling 196

Modeling Machine Learning Testing Metrics 196

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). The Core Responsibilities of the AI Product Manager.

Marketing 363

Marketing Experimentation Metrics Testing 363

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing can be done through various methods, such as data profiling, Statistical Process Control, and quality checks. Are problems with data tests?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. However, because most institutions lack a modern data architecture , they struggle to manage, integrate and analyze financial data at pace.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

Alation

FEBRUARY 3, 2022

They make testing and learning a part of that process. Using this methodology, teams will test new processes, monitor performance, and adjust based on results. In order for data governance to continuously improve , practitioners need to think of data governance as a cyclical process. Monitor and Measure Curation.

Data Governance 98

Data Governance Measurement Metadata Testing 98

AWS Big Data

FEBRUARY 13, 2023

Test environment In order to be confident with the performance of the RA3 nodes, we decided to stress test them in a controlled environment before making the decision to migrate. To do this, we required the following: A reference cluster snapshot – This ensures that we can replay any tests starting from the same state.

Snapshot 67

Snapshot Data Warehouse Testing Analytics 67

DataKitchen

JUNE 24, 2021

So we really prioritized the data that we thought had the biggest chance of delivering success in the end. Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It DataOps Enables Your Data Mesh or Data Fabric. Bergh added, “ DataOps is part of the data fabric.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

erwin

APRIL 15, 2020

If we reflect on the coronavirus example, we can ask: How do individual countries report their data? Do individual countries use the same testing protocols? Are infections universally defined the same way (based on widely administered tests or only hospital admissions)? erwin Data Intelligence for Data Governance and Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

O'Reilly on Data

MARCH 31, 2020

The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 339

Management Machine Learning Experimentation Metrics 339

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? Measurement and Reporting X X.

Management 79

Management Risk Measurement Optimization 79

AWS Big Data

NOVEMBER 16, 2023

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge and adherence to battle-tested best practices, and using the right tools and features in the right scenario. system implemented with Amazon Redshift.

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

CIO Business Intelligence

FEBRUARY 2, 2024

That’s where MDM comes in to help create a single version of truth across all copies of master data to ensure data values are aligned. Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers you have the right skillset. Informatica Master Data Management 10.3

Management 109

Management Data Governance Cost-Benefit Testing 109

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

Andrew White

JANUARY 11, 2021

See Roadmap for Data Literacy and Data-Driven Business Transformation: A Gartner Trend Insight Report and also The Future of Data and Analytics: Reengineering the Decision, 2025. measuring value, prioritizing (where to start), and data literacy? Storytelling is a nice one to use early on to test the approach.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

FEBRUARY 17, 2023

The firms that get data governance and management “right” bring people together and leverage a set of capabilities: (1) Agile; (2) Six sigma; (3) data science; and (4) project management tools. The overall program should set a 2-year vision, mission, and goals, and then focus on execution, measuring progress along the way.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64