Cloud has been the most significant technology that has enabled the growth of various businesses of all sizes. It offers numerous benefits without paying any additional cost or making new investments in hardware and infrastructure. Companies today generate vast volumes of data and to drive insights out of this Data, they need to inevitably leverage data analytics. Data analytics helps in driving business growth by enhancing their services and gaining a competitive edge. Larger companies can successfully analyze and gain data insights internally, but smaller companies often rely on external third-party sources to obtain data insights. To eliminate this external dependency for data insights, Cloud computing service providers can be of great help.
Defining Cloud Computing
With Cloud computing, companies can access different services such as databases, servers, and software. Companies can set up and run their applications with data center providers by incurring minimal additional costs. With Cloud computing combined with Data Science, companies can handle complex projects at very minimum prices, which would have else been a costly affair. Cloud computing has made Data Analytics so much simpler for the Data Scientists.
Why Cloud Computing for Data Science?
For companies, establishing servers for their data can be an expensive option. However, larger companies may manage to bear the server costs, but it becomes difficult for smaller firms with limited cash resources. Also, smaller firms need space for keeping these servers. These traditional data servers need regular maintenance and timely backups.
Cloud computing can be a great alternative to consider for overcoming the above concerns. By availing the services of some leading cloud service providers like ESDS, companies can host their data without being worried about servers. Companies can access the server architecture present in the Cloud as per their needs and pay only for the data/service that they require on the Cloud. Cloud has made data accessible to everyone in unique ways. Companies can perform data analytics with ease and compete on the global level without being concerned about the extra costs related to Data Science. Due to its growing popularity, Cloud computing and Data Science have given rise to Data as a Service or DaaS.
Data as a Service (DaaS)
The concept of Data as a Service or DaaS is gaining immense popularity owing to Cloud-based services. The vendors often provide DaaS for leveraging Cloud computing for several key data processes such as storage, processing, and analytics through a networked connection. Companies use Data as a Service to understand their target audience, automate key production processes, develop better products, etc. All these processes and methods help companies to enhance their profitability and better edge over the competitors.
DaaS can be seen on similar lines to IaaS, PaaS, SaaS, or any other common services existing today in the technological world. Talking in particularly about DaaS, it is much a newer concept. Earlier, the companies used to manage only a certain amount of data with no data processing and analytics carried out on a large scale. However, with the advent of Cloud Computing companies, DaaS is being used extensively and making it easy to manage the large volumes of data being processed. Enhanced Cloud storage and improved bandwidth services have resulted in making Data as a Service as the next big thing in the tech domain.
What if- No Cloud Computing for Data Science?
In the absence of Cloud computing, the Data Scientists would be forced to store their data on the local servers. Every time a Data Scientist would require some data for doing analysis, they would have to extract data from the servers to their systems. Transferring data from traditional servers to systems may involve many complications as companies today manage huge volumes.
