What is Data Science?

Data Science can be broken down into three main categories. These three categories are Business Intelligence, Traditional Methods, and Machine Learning. Let's get started and break down each one to see exactly what each category is.

Business Intelligence

Business Intelligence uses data to create reports and dashboards that will gain business insights.

The information that gets extracted from the data will be shown in forms of metrics, KPI's, reports and dashboards. This type of Data Science is most commonly used for price optimization and inventory management. Business Intelligence also comes under a few different names such as BI, Business Analysis and even mistaken as Data Analysis.

Traditional Methods

Traditional Method falls under Data Analysis/Analytics it assesses potential future scenarios by using advanced statistical methods.

The type of information you extract and create with traditional methods are Logical Regression charts, Clustering, Factor Analysis, and Time Series. This type of Data Science is commonly used for user experience and sales forecasting.

Traditional Methods also have a few different names such as Data Analysis, Big Data Analysis, Statistical Analysis or Advanced Analysis.

Machine Learning

Machine learning is the newest member of Data Science as it has only come into play over the last few years. Machine Learning is used to utilize artificial intelligence behavior in unprecedented ways.

There are three different techniques used within Machine Learning these are Supervised Learning, Unsupervised learning and Reinforcement learning.

Machine Learning is commonly used for Fraud Detection and Client Retention. Machine Learning also goes by Artificial Intelligence Analysis (AI Analysis) or is just known as Artificial Intelligence.

We are done! that sums up the basics of Data Science and what each category is and used for. If you have any questions feel free to use the contact form below.

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