Dataconomy

MAY 16, 2025

Advanced analytics has transformed the way organizations approach decision-making, unlocking deeper insights from their data. By integrating predictive modeling, machine learning, and data mining techniques, businesses can now uncover trends and patterns that were previously hidden.

Analytics 91

Analytics Analytics Big Data Analytics Big Data Analytics 91

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 139

Predictive Analytics Analytics Analytics Decision Trees 139

Dataconomy

APRIL 27, 2023

What is an online transaction processing database: Indexed data sets are used for rapid querying in OLTP systems Regular & incremental backups for data safety Frequent backups are necessary to ensure that data is protected in the event of a system failure or other issue.

Database 159

Database Data Scientist Data Mining Data Mining 159

Data Science Blog

JUNE 21, 2023

Cloud storage services like Amazon S3, Azure Blob Storage, or Google Cloud Storage provide highly scalable and durable storage options at a fraction of the cost of process mining storage systems. By utilizing these services, organizations can store large volumes of event data without incurring substantial expenses.

Big Data 130

Big Data Big Data Data Engineering Data Engineering 130

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

IBM Journey to AI blog

JULY 24, 2023

IT operations analytics (ITOA) vs. observability ITOA and observability share a common goal of using IT operations data to track and analyze how a system is performing to improve operational efficiency and effectiveness. It aims to understand what’s happening within a system by studying external data.

Analytics 69

Analytics Analytics Predictive Analytics Big Data 69

ODSC - Open Data Science

JANUARY 30, 2024

This is a pretty important job as once the data has been integrated, it can be used for a variety of purposes, such as: Reporting and analytics Business intelligence Machine learning Data mining All of this provides stakeholders and even their own teams with the data they need when they need it.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JUNE 25, 2023

Before delving deeper into the functionalities of business analytics, it is important to understand what business analytics is. The latter is the practice of using statistical techniques, data mining, predictive modelling, and Machine Learning algorithms to analyze past and present data. Lakhs to ₹ 15.3

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Alation

AUGUST 26, 2021

For this reason, data intelligence software has increasingly leveraged artificial intelligence and machine learning (AI and ML) to automate curation activities, which deliver trustworthy data to those who need it. How Do Data Intelligence Tools Support Data Culture? BI and AI for Data Intelligence.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

Mlearning.ai

MAY 23, 2023

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Data Science Blog

MARCH 30, 2023

Diese Anwendungsfälle sind jedoch analytisch recht trivial und bereits mit einfacher BI (Business Intelligence) oder dedizierten Analysen ganz ohne Process Mining bereits viel schneller aufzuspüren. Jedes Process Mining Tool benötigt pro Use Case mindestens ein Event Log.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147