Cloud Computing Outlook

Combining Cloud Computing & Big Data to Enhance Your Business

By Cloud Computing Outlook | Tuesday, January 07, 2020

Combining big data and cloud computing can open the pathway to infinite possibilities. The benefits of combining these two processes will also reveal how the two go hand in hand and enhance one another's functions

Fremont, CA: For someone in the field of cloud application development, big data and cloud computing are terms that they come across on a daily basis. The two go hand in hand, and most public cloud services today offer big data analysis as well. Software as a Service (SaaS) has become increasingly popular, and to remain popular, SaaS needs to keep up to date with the best cloud infrastructure practices and the different kinds of data that can be stored in large quantities.

Although the two subjects are technically different terms, they are often mentioned in the same breath as they interact synergistically with one another. Big data refers to large sets of data that are the result of a variety of programs. It can be used to indicate various kinds of data and data sets that are way too large to process on a primary computer. Any type of processing on a cloud platform, including big data analytics, is referred to as cloud computing. Cloud is a set of high powered servers that can view and query large sets of data much quicker than a regular computer. In short, big data refers to large sets of data collected. At the same time, cloud computing is the mechanism of taking this data in and performing various functions on the collected data set to derive results from the same.

Based on the Software as a Service model, cloud computing allows users to efficiently process large volumes of data, typically with the help of a console that can carry out specialized commands and set up paramet

ers, also available from the site's user interface. Some of the products included under this package are database management systems, cloud-based virtual machines and containers, identity management systems, machine learning capabilities, and more. Meanwhile, big data is often generated by large, network-based systems, which can either be in a standard or not standard format. When the data in hand is in a non-standard format, artificial intelligence from the cloud computing provider may be used along with machine learning to standardize the data.

Once the data is standardized, it can be further processed through the cloud computing platform and utilized in a variety of ways. Cloud infrastructure boats of the ability to process big data in real-time. Its ability to take massive blasts of data from intensive systems and process them in real-time makes it stand out from the traditional methods of data processing. With this new technology, big data analytics can now take place within a fraction of the time it used to take earlier.

Combining big data and cloud computing can open the pathway to infinite possibilities. The benefits of combining the two processes also reveal how the two go hand in hand and enhance one another's functions. Only having big data would leave users with large volumes of data that would take ages to process in the traditional methods and even longer to interpret. Add cloud computing to the picture, and you can use state of the art infrastructure and only pay for the time and power that you use. In many ways, cloud application development is fueled by big data, as without big data, there would be very little need for cloud-based applications.

Cloud computing services mainly exist due to the presence of big data, and similarly, big data exists because of the possibility to process them using cloud services. The two are, in many ways, a perfect match as they complement each other, and would cease to exist without one another. Both big data and cloud computing play a pivotal role in the digital society. Combined, the two provide people with great ideas but limited resources to have a chance at a successful business. It also enables established business to collect large volumes of data that it earlier had no means to process.

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