Intro to Data
In this section with introduce you to data, what is data, why is it important & where to store your data.
Data is the new oil - its value to you or your organization is not something to be underestimated. The big five tech companies, Amazon, Apple, Facebook, Google & Microsoft know this better than anyone. They collect vast amounts of data to help them better understand their customers.
In this tutorial you will learn:
- 1.What is data?
- 2.What is a database?
- 3.Differences between spreadsheets and databases
Data is a collection of facts such as numbers, words, measurements, observations or just a description of things. For example, a list of stock prices, medical records such as patients ages & heights & so on is all data.
A collection of stock price data
Data is most commonly represented in a table format - like an Excel spreadsheet. But data is more commonly stored inside a database.
A database is exactly like a collection of spreadsheets. Each spreadsheet will have some data inside of it. For example Exchanges, Stock Prices, Tickers, User data etc.
The individual spreadsheets are called "Tables". This is because they look exactly like tables with a row of headings & values ("fields") in each of the columns.
There are a variety of tools that you can use to look at your data tables in a spreadsheet view.
Even though your data tables are like a spreadsheet, they are not actually spreadsheets. Databases do a lot more than spreadsheets. Let's compare spreadsheets & databases.
Whilst in a spreadsheet you can store data in lists & organize numbers, databases do a lot more.
All software applications should run using a database in the backend. Dittofi has designed an interface that allows anyone to build an app on top of a professional database without having to write code.
Ditto tip: the database that Dittofi uses is called PostgreSQL. This is one of the most commonly used open source databases in the world. It is used by enterprise developers at large organizations to manage securely protect & manage sensitive client data, for example banking data, medical records, supply chain etc.