
OLAP | Online Analytical Processing
OLAP systems typically store data in a multidimensional format, which allows users to slice and dice the data to see different relationships and trends.

ETL vs ELT
ETL and ELT are two data integration methodologies that are used to extract data from different sources, transform it into a consistent format, and load it into a data warehouse or data lake.

Information-Action Value Chain
The information-action value chain is a framework that helps organizations understand how information can be used to create value. It basically consists of three parts, namely before the methods, the methods and after the methods.

Dashboarding & Visualization
Visualization and dashboarding are two related concepts that are used to communicate data to audiences & stakeholders in a way that is easy to understand.

Structured Data & Unstructured Data
Structured data and unstructured data are two types of data commonly used in the field of data science. The type of data that is used depends on the specific application.

Prescriptive Analytics
Prescriptive Analytics helps explicitly link analysis to decision making by making recommendations on what we should do or what choice we should make to achieve a certain outcome. This analytical method involves integration of numerical optimisation techniques with business rules and even financial models.

Descriptive Analytics
Descriptive Analytics helps us describe what things look like or what happened in the past. It can take forms of simple aggregations or cross tabulations data.

EDA – Exploratory Data Analysis
Exploratory Data Analysis (EDA) is a statistical method that helps you understand your data by summarizing its most important features.

OLAP – Online Analytical Processing
OLAP systems typically store data in a multidimensional format, which allows users to slice and dice the data to see different relationships and trends.

Data Mart
Data Marts are a subset of a data warehouse that is tailored to the needs of a particular business unit or department. Data marts often contain data important to a specific business area, such as sales, marketing, or finance.