In this video, you will learn to, identify the many data sources present in a typical organization, identify the type of data commonly contained in each data source. Here's just an example of a couple of different things you would see in typical organizations listers in no way shape or form exhaustive of the different types of; Applications, Databases, Data Warehouses, Big Data Environments, Files, Content Managers, Database Tools and Environments. But this is an example of all the different things that have to do with data in your organization. All the different avenues for people to access the data. Typically, an organization, you won't just have database. The DBAs connect to you. You'll really have applications that connect to a back end database such as your HR system when people are on board and off board. Say even as a key PeopleSoft shipping logistics for your clients and make orders logistics of shipping it around the world to your clients. Just need time for their deadlines etc. All of that would be in Databases, Applications and you're really and your entire workforce is logging into, do their job day in day out. Data Warehouses are typically used for crunching numbers. They're oftentimes incredibly vast amounts of data such as Hadoop Hive or Amazon redshift or even the teaser and Exif Data purpose spill incredibly fast processors to do nothing but crunch data incredibly efficiently and fast. So exif date is really for crunching numbers if you want to think of it that way. Big Data environments oftentimes you'll see an organization. It is a massive amount of data. A lot of times people don't quite know what's in the data or what they're going to do with it. So lot of times you'll have legacy databases that events sunset and shut down. Somebody archive the information and put it somewhere. They don't quite know what to do with, so someone decides to throw it in Hadoop. Maybe, we'll start gaining more information about our customers, our clients, our products, how we do business, how we can do business better, how we can interact with all of them better. So all that information just kinda gets thrown into Big Data and the ideas oftentimes to simply start gaining value out of it. Later as you start slice looking into it. Cloud Environments simply different places to host your data versus on-prem being data center that you have set up control and have complete ownership of Database Tools simply for ways to interact with databases, oftentimes used by DBAs but it can be a variety of different things used for Content Manager, SharePoint, classical, and there's a lot of different types though and that could really be just about anything. If you're thinking of Enterprise Content Manager could be a project management tool or something like that. Basically sending file's certainly files you're probably more familiar with this than you might think of or realize. So even your download folder would be File shares. So Linux Unix Windows all the different files stored inside them would be in all share unstructured data when you connect to HTTP sites all of those would be unstructured data or it can be unstructured data. So Data Source Types; Distribute Databases, Data Warehouses, Big Data, File Shares. Distributed Database examples are; Oracle, DB2, Microsoft SQL Server, MySQL, Postgres list goes on and on. Big Data examples; Hadoop, MongoDB, BigTable. Data Warehouse examples; Netezza, Exadata, Amazon Redshift, and Apache Hive. Fileshare examples; "NAs" (Network Attached Storage), Network Fileshare such as; EMC or NetApp, and Cloud Shares such as; Google drive, dropbox.com, box.com, and Amazon's S3 storage. Thinking of the different database types, house look at distributed databases and data warehouses. Both of those are often consider structured data and we'll get into what that means in a minute. Big Data database examples are oftentimes semi-structured data. Mostly because oftentimes it's a lot of different structured data sources that don't have means to look at all of the different types of data that was thrown into it holistically, and I'll explain more about that in a minute. Let me go over structured and semi-structured data, and posture example simply unstructured data. So think of your download folder, you had reason to download it but that's really it, it could depend on all the different projects you're working on work, it could be your kids Project, working for the first time or something like that. All the different things you might download but no real structure to it whatsoever other than that.