Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. They can be again classified as random testing and optimization.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. More focused options are available for particular data sets.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

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 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

Rocket-Powered Data Science

JULY 7, 2019

7) Security (airports, shopping malls, entertainment & sport events). Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…).

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

CIO Business Intelligence

DECEMBER 22, 2022

Such teams tend to view analytic pipelines as analogous to lean manufacturing lines and regularly reflect on feedback provided by customers, team members, and operational statistics. Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 123

Analytics Machine Learning Software Data Quality 123

DataKitchen

OCTOBER 11, 2021

The DataOps pipeline you have built has enough automated tests to catch errors, and error events are tied to some form of real-time alerts. Historic Balance – compares current data to previous or expected values. Statistical Process Control – applies statistical methods to control a process.

Testing 152

Testing Metadata Dashboards Statistics 152

BizAcuity

MAY 7, 2019

Demand forecasting should be done on a scientific basis, and several facts and events that can have an impact on demand need to be examined, studied and taken into consideration to make an accurate forecast. Basis these discussions and findings, the demand was predicted and a rolling plan was prepared for the upcoming three months.

Forecasting 75

Forecasting IT Sales Statistics 75

Smart Data Collective

MARCH 23, 2020

Online shopping, gaming, web surfing – all of this data can be collected, and more importantly, analyzed. Most businesses prefer to rely on the insights gained from the big data analysis. With the help of data mining and machine learning, it is now possible to find the connections between seemingly disparate pieces of information.

Big Data 103

Big Data Recreation/Entertainment Data mining Optimization 103

BizAcuity

APRIL 28, 2019

By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future. Predictive Analytics, a form of advanced analytics is also making great breakthroughs in the solving the debt collection problem.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

datapine

NOVEMBER 27, 2019

That way, any unexpected event will be immediately registered and the system will notify the user. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. It’s an extension of data mining which refers only to past data.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jedox

JULY 31, 2018

First-generation EPM software tools enabled normal business users to view their data from various angles and store it safely in a database specialized for flexible planning, analytics, and reporting. Compared to today’s standards, analytics was often limited to trying to describe past events, hence the name, descriptive analysis.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Cloudera

NOVEMBER 30, 2017

They hold a series of well-attended industry events that focus advancing the art of modern analytics and big data. TDWI Research is a leading research and consulting firm that focuses on broadening the knowledge and success of BI professionals worldwide.

Strategy 40

Strategy Big Data Data mining Visualization 40

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Jet Global

MAY 9, 2024

EDA is a crucial first step in any data science project, as it helps data scientists gain insights into the data and informs further analysis or modeling. Machine learning algorithms can automatically detect and correct data anomalies, inconsistencies, and missing values, leading to higher data quality within the pipeline.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

BI-Survey

OCTOBER 23, 2019

New real-time security intelligence solutions are combining big data and advanced analytics to correlate security events across multiple data sources, providing early detection of suspicious activities, rich forensic analysis tools and highly automated remediation workflows. The most important current IT trends (n=332).

Big Data 49

Big Data Analytics Manufacturing Digital Transformation 49

Jet Global

MAY 1, 2023

Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Some cloud applications can even provide new benchmarks based on customer data. Standalone is a thing of the past. They can then pinpoint areas for improvement.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52