Next Level Savings by Migrating Data Storage to the Cloud
Cloud storage is a model of computer data storage in which the digital data is stored in logical pools. The physical storage spans multiple servers (sometimes in multiple locations), and the physical environment is typically owned and managed by a hosting company. These cloud storage providers are responsible for keeping the data available and accessible, and the physical environment protected and running. People and organizations buy or lease storage capacity from the providers to store user, organization, or application data.
Data is typically split into three types of structures:
The data that has a structure and is well organized either in the form of tables or in some other way and can be easily operated is known as structured data. Searching and accessing information from such type of data is very easy.
For example, data stored in the relational database in the form of tables having multiple rows and columns. The spreadsheet is an another good example of structured data.
The data that is unstructured or unorganized Operating such type of data becomes difficult and requires advance tools and softwares to access information.
For Example, images and graphics, pdf files, word document, audio, video, emails, powerpoint presentations, webpages and web contents, wikis, streaming data, location coordinates etc.
Due to unorganized information, the semi-structured is difficult to retrieve, analyze and store as compared to structured data. It requires software framework like Apache Hadoop to perform all this.
Modern business systems manage increasingly large volumes of data. Data may be ingested from external services, generated by the system itself, or created by users. These data sets may have extremely varied characteristics and processing requirements. Businesses use data to assess trends, trigger business processes, audit their operations, analyze customer behavior, and many other things.
This heterogeneity means that a single data store is usually not the best approach. Instead, it's often better to store different types of data in different data stores, each focused toward a specific workload or usage pattern.