Astera

MAY 6, 2024

What Is Data Mining? Data mining , also known as Knowledge Discovery in Data (KDD), is a powerful technique that analyzes and unlocks hidden insights from vast amounts of information and datasets. What Are Data Mining Tools? Type of Data Mining Tool Pros Cons Best for Simple Tools (e.g.,

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

MAY 30, 2024

Data analytics has several components: Data Aggregation : Collecting data from various sources. Data Mining : Sifting through data to find relevant information. Statistical Analysis : Using statistics to interpret data and identify trends. Veracity: The uncertainty and reliability of data.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Data Pine

NOVEMBER 27, 2019

Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

Data Pine

AUGUST 29, 2022

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. 7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel.

Big Data 105

Big Data Data Analytics Data Analytics Data Mining 105

The BAWorld

MAY 14, 2024

Prescriptive Analytics – This analytics prescribes the data to take corrective measures to make progress or avoid a particular event in future. Predictive Analytics – It uses Machine Learning models to predict future trends, events and outcomes. Write some key skills usually required for a data analyst.

Data Analytics 52

Data Analytics Data Analytics E-Commerce Visualization 52

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98