DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires. Measure success. Create tests.

Testing 152

Testing Dashboards Measurement Experimentation 152

Cloudera

FEBRUARY 16, 2022

blueberry spacing) is a measure of the model’s interpretability. This allows data scientists, engineers and data management teams to have the right level of access to effectively perform their role. Model performance metrics together with input features, predictions and potentially ground truth values, can be tracked over time.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

DataKitchen

APRIL 13, 2021

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. QuerySurge – Continuously detect data issues in your delivery pipelines. Production Monitoring Only.

Testing 300

Testing Machine Learning Consulting Data Quality 300

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Occam's Razor

MARCH 23, 2010

Too many new things are happening too fast and those of us charged with measuring it have to change the wheels while the bicycle is moving at 30 miles per hour (and this bicycle will become a car before we know it – all while it keeps moving, ever faster). You'll have no time for data analysis, certainly not for data actioning. ~

Analytics 118

Analytics Consulting Metrics Experimentation 118

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66