O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. Not even close.

Modeling 134

Modeling Finance Uncertainty Data mining 134

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Crisis management and risk management: Text mining serves as an invaluable tool for identifying potential crises and managing risks.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Smart Data Collective

SEPTEMBER 21, 2022

As far as Data Analysis is concerned, potential employees should have an extensive knowledge of quantitative research, quantitative reporting, compiling statistics, statistical analysis, data mining, and big data.

Statistics 85

Statistics Software Data mining Marketing 85

CIO Business Intelligence

MARCH 24, 2023

A framework for managing data 10 master data management certifications that will pay off Big Data, Data and Information Security, Data Integration, Data Management, Data Mining, Data Science, IT Governance, IT Governance Frameworks, Master Data Management

Data Governance 142

Data Governance Management Metadata Data Quality 142

BizAcuity

MARCH 31, 2022

Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management. A lot of testing AI methods can be utilized for better and more accurate outcomes from mining the data.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Smart Data Collective

MAY 15, 2019

They use a variety of data mining tools to make this possible. These messages might encourage the recipient to take some sort of action that can lead to further data exploitation. . #1 Bluebugging.

Big Data 93

Big Data Risk Measurement Data mining 93

CIO Business Intelligence

MARCH 13, 2024

La base imprescindibile restano i big data, perché il machine learning ha bisogno di dataset molto estesi. Anche le questioni di privacy e sicurezza sono aspetti che i CIO dovranno valutare per gli impatti sulla compliance e le attività di risk management.

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

datapine

MARCH 31, 2022

BI Data Scientist. A data scientist has a similar role as the BI analyst, however, they do different things. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis. SAS BI: SAS can be considered the “mother” of all BI tools.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Jet Global

MAY 9, 2024

This data is transformed, cleansed, and loaded into a data lake or warehouse for analysis. Finance organizations can then leverage advanced analytics and machine learning applications to gain valuable insights for strategic planning and risk management.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

bridgei2i

JULY 28, 2020

So, then we need systems, analysts, database administrators, people who can set in place, these types of backup systems for risk management. In my company StatWeather we use this kind of data and data mining to forecast weather and climate patterns, which has been very successful.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98