DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

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?

Data Governance 92

Data Governance Risk Data-driven Measurement 92

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

IBM Big Data Hub

DECEMBER 4, 2023

Clearly define the objective of the implementation project and determine its scope, timeline and budget as well as create a risk management plan. This is also the time to determine which data will be migrated, as some older data may be best stored in a secure archive.

Testing 72

Testing Consulting Digital Transformation Cost-Benefit 72

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.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218