What is Data from Business Intelligence prespective?

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     Every newbie in the Business Intelligence domain has these questions, What is Data? Why everything revolves around Data? What is the importance of Data?

    The key to understand Business Intelligence is through understanding data. The first thing you should know is anything can be data. It can be a document or any comment posted on social media or any video even movement of your cursor can also be stored as data. Data is a value or information about any entity that has various forms, can be stored and used to get an insightful picture of the entity. 

    We are in a digital world today where people are more connected to each other through phones and computers. Everything we type or record or hover is the source of data nowadays. Once the data is captured then we try to understand it with various processes and tools. When we understand it we notice the different insights of the entity which lead us to make better future decisions. Humans make decisions on facts and experience and machines can do the same with data. Hence data is important!



   Data is majorly categorised into two types Relational data and Non-Relational data. Relational data are also called Structured data. Stored in the form of rows and columns called tables, easy to store,  understand and manage relations. To manage this type of data we require a query language SQL(Structured Query Language). Non- Relational data has different shapes and sizes of data that cannot be stored in a specific format. It is also called Non-Structured data. The data comes in all different shapes and sizes. Example of data is Videos, audios and documents.

  After knowing what is data now we need to know where we should store it, the answer is Database! Since all of the data cannot be stored in one single database, we have different types of database. For storing relational data we have a Relational database for Non-Relational data we have a Non-Relational database. Four crucial properties define the relational database transaction: Atomicity, Consistency, Isolation and Durability we refer to it as ACID properties of Relational database. Examples of a relational database are Microsoft SQL Server, MySQL, PostgresSQL etc. A non-relational database does not use the tabular schema of rows and columns like a relational database. Rather, its storage mode is optimized for the type of data it's storing. Example of the non-relational database is MongoDB, Redis etc.

    How to handle different form of incoming data? In technical term, categories of data are called Data type. The other important aspect is the size of the data. For example, for a relational database based on these two factors, there are different data types available below that are mostly used once:

  1. Int - small numeric values from -2,147,483,648 to 2,147,483,647.
  2. Decimal - Numeric values with a large decimal point from -10^38 +1 to 10^38 -1.
  3. Char - Maximum length of 8,000 characters. ( Fixed length non-Unicode characters).
  4. Varchar - Maximum of 8,000 characters. (Variable-length non-Unicode data).
  5. Nvarchar - Maximum length of 4,000 alpha characters.(Variable-length Unicode).
  6. Text - Variable-length non-Unicode data with a maximum length of 2,147,483,647 characters.
  7. Float - Numeric values with large decimal point from -1.79E + 308 to 1.79E + 308.
  8. Boolean - True or False values.
  9. Date -Stores a date like June 30, 1991
  10. Time - Stores a time of the day like 12:30 P.M.

   Hope this blog will help you gain a different perspective of data. Happy Learning!

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