FineReport

APRIL 21, 2024

The increasing adoption of cloud-based technologies is resulting in the migration of BI tools to SaaS platforms, marking a pivotal shift towards cloud-based data analysis. However, SaaS BI tools address this challenge by offering user-friendly interfaces that simplify the process of data preparation, modeling, and analysis.

Business Intelligence 52

Business Intelligence Visualization Dashboards Data-driven 52

CIO Business Intelligence

JUNE 7, 2022

Sentiment analysis: Sentiment analysis uses tools such as natural language processing , text analysis, computational linguistics, and so on, to understand the feelings expressed in the data. Data analytics vs. business analytics. Business analytics is another subset of data analytics.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

O'Reilly on Data

DECEMBER 12, 2019

Residual analysis is another well-known family of model debugging techniques. Residuals are a numeric measurement of model errors, essentially the difference between the model’s prediction and the known true outcome. Interpretable ML models and explainable ML. Residual analysis.

Machine Learning 197

Machine Learning Modeling Testing Risk Management 197

FineReport

APRIL 9, 2024

The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance. Furthermore, maintaining data security and compliance requires continuous vigilance and proactive measures to safeguard against potential vulnerabilities.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Integrate the data sources of the various behavioral attributes into a functional data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

DataKitchen

SEPTEMBER 21, 2023

There are multiple locations where problems can happen in a data and analytic system. What is Data in Use? Data in Use pertains explicitly to how data is actively employed in business intelligence tools, predictive models, visualization platforms, and even during export or reverse ETL processes.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. Applying data integrity constraints on live, incoming data streams could have the same benefits.

Modeling 226

Modeling Machine Learning Predictive Modeling Consulting 226

CIO Business Intelligence

MAY 10, 2022

By applying machine learning to the data, you can better predict customer behavior. Gartner has identified four main types of CDPs: marketing cloud CDPs, CDP engines and toolkits, marketing data-integration CDPs, and CDP smart hubs. Treasure Data CDP. Customer data platform vs. CRM. Types of CDPs.

Advertising 122

Advertising Interactive Marketing Structured Data 122

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.

Insurance 86

Insurance Risk Data-driven Finance 86

Cloudera

NOVEMBER 2, 2020

It is a type of data warehouse modernization that lets you have “small data” semantics and performance at “big data” scale. the data arrives into the warehouse faster – think streams of many millions of events per second constantly arriving. Data Hub – Streams Messaging Template. Data Hub – .

Data Warehouse 100

Data Warehouse Optimization Dashboards Interactive 100

Smarten

AUGUST 6, 2024

According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc.,

Predictive Modeling 64

Predictive Modeling Key Performance Indicator Data-driven Finance 64

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 1, 2023

Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports. How to measure the value. Cons It is not clear how to measure the revenue impact of the analytics offering. Analytics pricing can be based on the number of users, overall system usage, or a fixed dollar amount.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52