Modeling a database using the Star Schema, applied to the context of "CFB Pharmacy", which seeks to develop decision support systems for revenue analysis. The project was carried out in two stages: ...

Finally, DBAs will be at the center of collaboration across teams involved in supporting and using the data lakehouse. Lakehouses break down silos between data engineering, analytics, and data science ...

With the number of data breach victims up nearly 500% in 2024, Experian provides six steps to take if your information is compromised.

For the first time, data processing shifts from ETL to ELT, meaning one can do all data modeling in the warehouse instead of preprocessing it in HDFS/any intermediary data pipeline.

Data preprocessing is a foundational step that has a profound impact on the accuracy and reliability of analytical outcomes. This process involves converting raw, unorganized data into a clean, ...

Data preprocessing plays a critical role in the success of machine learning and deep learning models in the medical and healthcare field. As the availability of healthcare data continues to grow, ...

However, if the teams involved in testing do not trust their test environments or the provisioned test data, testing is less valuable and test results are more likely to be met with scepticism.

Doing so can help you win over allies and generate buy-in to continue the data intelligence journey. These are just the initial steps, and this will not be a quick process.