From the course: Introduction to Career Skills in Data Analytics

Data sources and structures

From the course: Introduction to Career Skills in Data Analytics

Data sources and structures

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- We hear about data all the time, right? But what does that really mean? Let's start with the basics. Data has a value, like your birthday, that's a value like November 20th of any year. So your birthday would be 11/20 of that year. Data has a type, like birthday. It's a date data type. And data has a field name, like DOB, for Date of Birth. When we put these fields together, like First Name, Last Name and Date of Birth, we're creating a record. People use records and spreadsheets all the time, but they don't really think of the sheet as a table, but it actually is. It's just a table called Sheet One. And when fields are combined in a database, they're stored in tables. They still have names, values, and data types. And when we fill in this information for a person, we're creating a record. Tables are a great way to capture multiple types of data in a structured way. This way of storing data is way more flexible than the spreadsheet environment. There are also other types of systems that collect and store data for the analysts to use for their reporting requirements. This varies of course by company, but you can expect to find spreadsheets, databases or even data warehouses. Data warehouses really are data systems that have the refined tables from our production systems, like the purchasing system, for example. A customer-dedicated software system might have a database with hundreds of tables and details, but only certain tables and fields are needed for reporting. These fields get cleaned up by data warehousing professionals and brought into the warehouse for storage and safekeeping. It is a valuable source of nicely structured data that has been vetted for the analysts to begin their reporting projects. Structured data that fits neatly into tables and feeds a beautifully designed warehouse is amazing, but not all data is structured. This is where systems like data lakes help organizations capture data so they're storing it before it's actually refined for reporting needs. Data warehousing and data lakes and even data lake houses are very interesting. And if you're into designing databases or designing data solutions, you may find you want to explore these skills further. Data analysts will tap into these systems for the data. They don't necessarily create them. As a data analyst, you will find yourself working with various systems and file types. At the start of your career, you can expect a lot of spreadsheets and CSP files as you work your way up into working with data stored in larger data systems. And don't worry, no matter the level, most data professionals love a good spreadsheet when it's used for analysis and not for storing data.

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