CIO Business Intelligence

SEPTEMBER 2, 2022

Back-end software engineers are responsible for maintaining the structure of server-side information by optimizing servers, implementing security measures, and developing data storage solutions. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Back-end software engineers are responsible for maintaining the structure of server-side information by optimizing servers, implementing security measures, and developing data storage solutions. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses. Conclusion.

Risk 52

Risk Modeling Metrics Business Objectives 52

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

erwin

FEBRUARY 4, 2021

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Large projects or those involving text, images, or streaming data may need specialized infrastructure. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Cloudera

SEPTEMBER 7, 2023

This puts the onus on institutions to implement robust data encryption standards, process sensitive data locally, automate auditing, and negotiate clear ownership clauses in their service agreements. But these measures alone may not be sufficient to protect proprietary information. AI-ify risk management.

Insurance 78

Insurance Risk Data-driven Finance 78

Octopai

JULY 12, 2020

Like many BI teams, FCSA’s struggles began with the massive amount of data that existed in their enterprise data warehouse. Perhaps most frustrating for FCSA was the major data-quality issues that arose due to manual, error-prone data processing. Think of the wonders it could work for your enterprise.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

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

AUGUST 29, 2022

However, once you start working with larger enterprise-level data sets with millions of rows and hundreds of columns of information, Excel may not be capable of handling such volumes. Topics covered here range from backtesting and benchmarking approaches to data quality issues, software tools, and model documentation practices.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

datapine

FEBRUARY 22, 2022

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. A planned BI strategy will point your business in the right direction to meet its goals by making strategic decisions based on real-time data. It’s that simple.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

AUGUST 14, 2023

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? To answer questions such as these and plan accordingly, organizations must implement data product portfolio management (DPPM).

Management 81

Management Risk Measurement Optimization 81

Andrew White

JANUARY 11, 2021

What is your vision for D&A for small and medium enterprises? We have specific research for midsize and small enterprises. See 3 Questions That Midsize Enterprises Should Ask About Data and Analytics and have an inquiry with Alan Duncan. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52