Dataconomy

DECEMBER 17, 2024

Example: For a project to optimize supply chain operations, the scope might include creating dashboards for inventory tracking but exclude advanced predictive analytics in the first phase. Key questions to ask: What data sources are required? Are there any data gaps that need to be filled?

Data Quality 91

Data Quality Power BI Data Engineering Data Engineer 91

Pickl AI

DECEMBER 2, 2024

Understanding these enhances insights into data management challenges and opportunities, enabling organisations to maximise the benefits derived from their data assets. Veracity Veracity refers to the trustworthiness and accuracy of the data. Value Value emphasises the importance of extracting meaningful insights from data.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Understanding these enhances insights into data management challenges and opportunities, enabling organisations to maximise the benefits derived from their data assets. Veracity Veracity refers to the trustworthiness and accuracy of the data. Value Value emphasises the importance of extracting meaningful insights from data.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JUNE 4, 2024

Application of Data Science in Healthcare Data Science in healthcare revolutionizes patient care by enabling early disease detection, personalizing treatment plans, optimizing hospital operations, and enhancing patient engagement. Example: Predicting Heart Disease Heart disease is a leading cause of death worldwide.

Data Science 52

Data Science Big Data Analytics Big Data Analytics Predictive Analytics 52

Pickl AI

OCTOBER 15, 2024

Predictive Analytics Predictive analytics involves using statistical algorithms and Machine Learning techniques to forecast future events based on historical data. It analyses patterns to predict trends, customer behaviours, and potential outcomes.

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. What Are Some Common Tools Used in Business Intelligence Architecture?

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Data Science Blog

JULY 23, 2023

BI provides real-time data analysis and performance monitoring, while Data Science enables a deep dive into dependencies in data with data mining and automates decision making with predictive analytics and personalized customer experiences.

Data Science 246

Data Science Azure Power BI Business Intelligence 246