Data types, collection, and storage forms

Data in the 21st Century is like Oil in the 18th Century: an immensely. Data is the fuel that can drive a business to the right path or at least provide actionable insights that can help strategize current campaigns, easily organize the launch of new products, or try out different experiments. In this article we will discuss Data types, collection and storage forms.

Types of data

? Qualitative Data: Qualitative or Categorical Data describes the object under consideration using a finite set of discrete classes. It means that this type of data can’t be counted or measured easily using numbers and therefore divided into categories.

Place of production is an example for this type of data (Egypt, China, Europe, ....). These categories help us deciding which encoding strategy can be applied to which type of data. Data encoding for Qualitative data is important because machine learning models can’t handle these values directly and needed to be converted to numerical types as the models are mathematical in nature. There are two subcategories under this type:

1. Nominal Data: These are the set of values that don’t possess a natural ordering. The gender of a person is another one where we can’t differentiate between male and female with values.

2. Ordinal Data : These types of values have a natural ordering while maintaining their class of values. If we consider the size of some objects then we can easily sort them according to them in the order of small, medium, large.

? Quantitative Data: This data type tries to quantify things and it does by considering numerical values that make it countable in nature. The price, discount offered, number of ratings on a product, the frequency of processor, or ram size are all examples for this type. It also has two subcategories:

1. Discrete: The numerical values which fall under are integers or whole numbers are placed under this category. The number of employees is an example.

2. Continuous: The fractional numbers are considered as continuous values. These can take the form of the operating frequency of the processors for example.

Methods to collect Data

There are various methods of collecting primary, quantitative data. Some involve directly asking customers for information, some involve monitoring your interactions with customers and others involve observing customers’ behaviors. The most efficient way to use depends on your goals and the type of data you’re collecting. Here are some of the data collection methods:

1. Surveys: in which you can directly ask customers for information.
2. Online Tracking: Your business’ website, and your app if you have one, are excellent tools for collecting customer data. When someone visits your website, you can see how many people visited your site, how long they were on it, what they clicked on and more.
3. Transactional Data Tracking: web stores owners may store transactional records in a customer relationship management system. This gives them insights about how many products they sell, what types of products are most popular, ...etc.
4. Social Media Monitoring: people’s opinion and daily talks on social media can help you to get their needs, likes, and dislikes.
5. In-Store Traffic Monitoring: The easy way to do this is with a traffic counter on the door to help you keep track of how many people come into the store during the day. This data will give insights about busiest days and hours. Also with help of some sensors, you can find the most popular department at the store.

Data Storage

Data storage essentially means that files and documents are recorded digitally and saved in a storage system for future use. Storage systems may rely on electromagnetic, optical or other media to preserve and restore the data if needed. Data storage makes it easy to back up files for safekeeping and quick recovery in the event of an unexpected computing crash or cyberattack. Data storage can occur on physical hard drives, disk drives, USB drives or virtually in the cloud. There are three forms to store data in:

1. File storage: File storage, also called file - level or file - based storage, is a hierarchical storage methodology used to organize and store data.
2. Block storage: Block storage, sometimes referred to as block - level storage, is a technology used to store data into blocks. The blocks are then stored as separate pieces, each with a unique identifier. Developers favour block storage for computing situations that require fast, efficient and reliable data transfer.
3. Object storage: Object storage, often referred to as object - based storage, is a data storage architecture for handling large amounts of unstructured data. This data doesn't conform to, or can't be organized easily into, a traditional relational database with rows and columns. Examples include email, videos, photos, web pages, audio files, sensor data, and other types of media and web content (textual or non-textual).

Written By: Hadeel Sameh