datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. Exclusive Bonus Content: How to be data driven in decision making?

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

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. Returning to previous anti-bias and AI transparency tools such as Model Cards for Model Reporting (Timnit Gebru, et al.)

Management 253

Management Metrics Machine Learning Modeling 253

AWS Big Data

MARCH 7, 2023

ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. Unlike ingestion processes, data can be transformed as per business rules before loading. You can apply technical or business data quality rules and load raw data as well.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

O'Reilly on Data

JULY 15, 2019

Regulators behind SR 11-7 also emphasize the importance of data—specifically data quality , relevance , and documentation. While models garner the most press coverage, the reality is that data remains the main bottleneck in most ML projects. Model monitoring. Governance, policies, controls.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

AWS Big Data

AUGUST 14, 2023

Trunk (core data products) – Core data products are those that are central to the organization’s ability to function, and from which the majority of other data products are derived. Organizational governance for these data products typically favors availability and data accuracy over agility.

Management 79

Management Risk Measurement Optimization 79

Grooper

AUGUST 19, 2019

Traditional data sources like end of month statements and quarterly reports are no longer enough. It includes the reports, charts, dashboards, and terminology unique to your organization. ISL helps today's business leaders understand how data answers business questions. Key Language of Applied Analytics.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Occam's Razor

AUGUST 22, 2011

Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. Convert Data Skeptics: Document, Educate & Pick Your Poison. Data Mining And Predictive Analytics On Web Data Works? Refuse Report Requests.

KPI 124

KPI Metrics Measurement ROI 124