Data in the Cloud cannot be considered as Big Data

 The terms "Data in the cloud" and "Big data" are often used interchangeably. One may believe they have the same meaning, but this is far from the truth. To understand the difference between these two, you must first have basic knowledge about them.

Data in the cloud means the data stored in the cloud. When the person thinks about cloud storage, they will likely think about storing files (for instance: songs, videos, and applications) on a remote server that you can retrieve from multiple devices. Cloud storage is essentially a system that allows you to store data on the Internet, as you would save on a computer. Whether you talk about Google Drive, DropBox, or iCloud, the definition of cloud storage remains the same. It allows you to upload data through the Internet to cloud-based servers. Once you store your data on the cloud, you, or any other person you give access to, can access it from multiple devices using the Internet as a medium. Best Cloud Storage Systems include: Google Drive, Dropbox Business, OneDrive, Apple iCloud, Dropbox, and Box.

In simple layman's terms, Big Data is a large amount of structured, unstructured, semi-structured data that you can use for analysis purposes. It is a term used to describe data that is huge in amount and which keeps growing with time. You can utilize this data to track and mine information for analysis or research purposes. Big Data is more of a marketing word. It signifies that the Data today is so Big that you cannot examine all of it at once due to the amount of memory (RAM) available that will be required to hold the Data. Data is a lot more than the memory available. This data is generated in High Volume, velocity, and variety.

Are Big data and the cloud – a perfect match?

Big data projects typically get started with data storage and the application of basic analytics modules. However, as you find concepts to extract data at a much larger scale, you will need to find better methods to process and analyze data, in which you will likely require infrastructure upgrades.

You may add more functions to your in-house data warehouse or power up more servers to cater to the rapidly-increasing analytics necessities. But even with the hike of your on-premise systems, your base eventually may not be able to sustain. This is where the cloud comes in, or big data goes to the cloud.

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