IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

IBM Big Data Hub

FEBRUARY 23, 2024

Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends. These AI-driven systems can manage a customer journey from routine inquiries to addressing more complex and data-sensitive tasks.

Enterprise 96

Enterprise Interactive Data-driven Key Performance Indicator 96

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 79

Marketing Technology Advertising ROI 79

datapine

JANUARY 6, 2022

Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and labeling of data into identifiable themes. Predictive analysis: As its name suggests, the predictive analysis method aims to predict future developments by analyzing historical and current data.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Data Science 101

OCTOBER 31, 2019

Data Collection. After defining the goals in the previous step, it is essential to collect data. This could involve using data that already exists in a company’s database, getting data from external resources or steps to collect new data through survey forms filled by customers. Regression.

Data mining 77

Data mining KDD Data Science Forecasting 77

IBM Big Data Hub

AUGUST 7, 2023

It offers enhanced capabilities to analyze complex and large volumes of comprehensive recruitment data to accurately forecast enrollment rates at study, indication, and country levels. AI models can be designed to detect anomalies in real-time site performance data.

Optimization 55

Optimization Forecasting Data-driven Strategy 55

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Sisense

JUNE 9, 2021

Like every other business, football has experienced rapid technological advances that generate and capture data from training and match play. And also like their counterparts in the business world, coaches are relying on metrics to guide their decision-making. Gleaning actionable intelligence from disparate data sources.

Analytics 98

Analytics Data-driven Internet of Things Measurement 98

Jet Global

MAY 21, 2020

In addition to the traditional budget considerations, future trends in education — such as the rapid growth of online learning, digital credentialing, smart campuses, wireless presentations, and predictive analytics — will require financial analysis to determine where the institution’s money should be spent. Admissions and enrollment.

Finance 98

Finance KPI Forecasting Data-driven 98

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Organizations using C360 achieved 43.9% reduction in sales cycle duration, 22.8%

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Domino Data Lab

JULY 22, 2019

You know, case in point, if you were to talk about predictive analytics 20 years ago, the main people in the field would have laughed you out of the room. Predictive analytics, yeah, not so much.” How can you trace that all the way back into the data collection?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

MARCH 18, 2021

There will be an increased volume of data storage required, due to the longer history needed by the ES approach to risk measurement. And there will be expansions on the requirements for managing and monitoring both data lineage and data security. 30x increase in computational requirements. .

Risk 56

Risk Machine Learning Risk Management Measurement 56

Smart Data Collective

OCTOBER 25, 2023

BI guides decision-makers through data, enabling insights from vast information. Essentially, it organizes and analyzes data, supports informed decisions, and offers real-time access, predictive analytics, and intuitive visualization.

Key Performance Indicator 94

Key Performance Indicator Business Intelligence Data-driven Metrics 94

datapine

JANUARY 31, 2022

They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes. Overall, the use of data analysis in this use case showed a significant increase in employee collaboration and increased operational efficiency for the company.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Jet Global

MAY 1, 2023

Business End-User Benefits Embedding analytics into essential applications makes analytics more pervasive. As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. Use the experts in analytics to add value to your product.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52