In this video, you will learn to describe various data source types such as distributed databases, data warehouses, big data, and file shares. Well, this is Chris Winn. I'm a cybersecurity specialist with IBM, also known as a security technical specialists. In this video, we will be covering key concepts of databases and database security. We'll also be giving an overview of data models such as structured, semi-structured, and unstructured data. While we will be covering unstructured data, such as file shares of network attached storage, the deeper dive into unstructured data, such as file shares, this is going to be covered in a separate video. This video we'll only cover enough to explain what they are, so you can have an understanding of the different types of data models. Every organization whether it's a public or a private entity has many different types of data sources, such as distributed databases, Microsoft SQL Server, Oracle, MySQL, SQL light, Postgres, the list goes on and on and on. It's probably the most common database type in the world. Also data warehouses such as Amazon's redshift or Hadoop's Hive or TISA or exit data. Very purpose built environments, and we'll talk a bit about those later founded for Databases Big Data NoSQL. We will cover those in a bit, but those you might be familiar with such as Google's BigTable or Hadoop and MongoDB. File shares. So file shares are everything from Amazon S3, Google Drive, Dropbox, Box.com, even your download folder on your laptop. That would be a file share, that would be a directory, but we'll cover those in a bit. So one thing every organization has in common is they're all using a lot of data in a variety of combinations of these things. They might be using all or only a couple of these. Also, organizations have many different locations oftentimes regardless of it's a public or private entity, it could be around the city, around the state, around the world. That's true regardless if it's a retail store, bank, a hospital, even a public building, even picking all the different locations, Amazon, and IBM and Google have around the world. One thing in common with all of these different entities, public and private, is they have a lot of Infrastructure and the backend that help them do what they do day in and day out, regardless if it's as simple as providing e-mail for the organization, providing check clients for the organization, even simply all the different projects going on in an organization, the project holders, what they're working on, the way teams integrate together. All the different backend systems being worked on our commonality in all organizations that all of that background infrastructure is stored in data centers. Now, it used to be in the early 2000's people still thought mainly of security as a perimeter defense, and by perimeter defense, I really mean firewalls and VPNs and stopping people from ever getting into your organization. It's been proven time and time again that that's just not adequate anymore if not in the current day and age because regardless of people trying to come into your organization, there's just so many different ways into an organization. You're not just trying to come through your firewall, they're not just trying to come through VPN. They're trying to come with your employees credentials. They're trying to come through your business partners, through other entities that you've worked with that have access into your data center. All of those different means of entering your data center are all potential threat vectors or ways into your organization that you have to think of and lock. Its essentially a safe with many, many different windows and doors that each I will need some security controls around. That's why so much focus has been given in the last 10 years to data security and all of the different bridges that you hear again and again and again, where all somebody compromising an organizations data security controls, or simply accessing it because of lack of controls access to the data.