From the previous blog post, I had explored how a company can go about sourcing for data and why databases are important. It’s really amazing how the MBA at LBS has now exposed me to the world of data analytics. Now we will dive into the categories of databases that we have, the criteria for choosing the best database for a given scenario, and the basics of how relational databases work.
Databases can be classified based on data type into three categories: structured data, unstructured data, and semi-structured data. Relational databases and non-relational databases are two types of databases that handle these data types differently.
Structured data is data that is organized in a predefined format, such as tables, spreadsheets, or forms. Examples of structured data include customer names, email addresses, phone numbers, product prices, date and time, etc. Structured data is easy to store, query, and analyze using relational databases and SQL.
Unstructured data is data that is not organized in a specific way, such as text, images, audio, video, or social media posts. Examples of unstructured data include email messages, word-processing documents, audio or video files, collaboration software, or instant messages. Unstructured data is difficult to store, query, and analyze using relational databases and SQL, and may require special tools or techniques to process.
Semi-structured data is data that has some elements of structure, but not enough to fit into a predefined format, such as XML, JSON, or HTML. Examples of semi-structured data include web pages, online reviews, tweets, or blog posts. Semi-structured data can be stored, queried, and analyzed using either relational or non-relational databases, depending on the complexity and variety of the data.
Relational databases store data in tables, which are composed of rows and columns with unique identifiers. Each row in a table represents a record or an entry, while each column represents an attribute or a field. A table can have one or more primary keys, which are attributes that uniquely identify each record in the table. A primary key can be either a natural key or a surrogate key. A natural key is a primary key that has significance in the real world, such as an employee’s social security number or a customer’s bank verification number (BVN). A surrogate key is a primary key that has no meaning in the real world, such as an employee ID number or a customer ID number.
A table can also have one or more foreign keys, which are attributes that can link the records in a table to another table in the database. A foreign key stores the value of the primary key of another table. For example, a branch ID can link an employee info table to a branch table, by storing the value of the primary key of the branch table. A table can also have a composite key, which is a combination of two or more columns that uniquely identify each record in the table.
Learning about how databases are structured has been a big eye-opener for me, as I had always wondered what databases were and how they worked. My research then took me into the realm of something called Structured Query Language (SQL). SQL is a standard language for interacting with relational databases and performing various operations on them. Learning this language is essential for being able to extract information from a database. With SQL, there are four core operations we can perform on a database:
Create: This operation allows us to create a new database, table, or record by specifying the name, structure, and data of the object.
Read or Retrieve: This operation allows us to view the data stored in the database, table, or record by specifying the criteria, filters, and order of the data.
Update: This operation allows us to modify the data stored in the database, table, or record by specifying the new values, conditions, and actions of the data.
Delete: This operation allows us to remove the data stored in the database, table, or record by specifying the criteria, filters, and actions of the data.
My Takeaway: The power of databases is phenomenal, as the insights from being able to analyze all the data generated by a business stored in a central location can be explosive. I have learned that leveraging technology to streamline business operations and improve efficiency is part of a manager’s responsibility, and this MBA program is exposing me to the use of tech via data analytics. For this, I say a big thank you to LBS.
