As you progress further, you’ll also need to plan your ETL processes. how your data will be extracted from various source systems, transformed to meet the desired format and quality standards, and loaded into the data warehouse. The goal here is to ensure that the data is cleansed, enriched, and made readily available for analytics.
The planning and design phase ends with setting up security policies and access controls to safeguard your data warehouse. It involves identifying what data is sensitive and needs to be taiwan whatsapp number data protected. You’ll also decide who can do what in the data warehouse. For example, some people might only be allowed to read data, while others might be able to make changes. Another technique to protect sensitive data is to keep it safe from prying eyes by encrypting it. So, even if someone tries to steal it, they’ll need to decrypt it to make sense of it.
Data Acquisition
As the name suggests, this stage focuses on gathering and preparing data for effective analysis. The first key task in this stage is data extraction. Here, you’ll be tasked with retrieving data from diverse source systems, which can range from relational databases and flat files to web-based APIs. Your goal is to efficiently pull data from these sources while considering factors like data volume, frequency of updates, and the specific data elements needed for analysis.