Do you know that the global business community will be spending $310 billion on the Internet of Things (IoT) by 2020?
Isn’t it a huge investment! Why is this trend booming?
Actually, the IoT has encapsulated devices. The software, sensors, actuators and connectivity through vehicles and home appliances are penetrating deeply. This networking model is skyrocketing in almost every walk of life. That’s why small entrepreneurs to big industrialists are hungry for the digital connectivity, interactivity and exchange of data over the internet.
Its reason is intelligence that underlies a massive set of data. The influx of data is expanding. If you possess the lens of an experienced data scientist, you can extract and mine that business intelligence via digging out patterns. Simply put, whatever size of data the IoTs produce, you can churn it in a few minutes using data mining software and tools.
Here, the biggest challenge is the progressive nature of data size. It’s massively sizing into amassed data. This is where the cloud computing comes in play.
I won’t be wrong, if I say that the cloud computing and IoT are closely paired. On one hand, the latter technology is piling a mountain of data, whereas the cloud computing is empowering them. As a virtual assistant, it is helping in processing the scaling up data. What state-of-art IT infrastructure the cloud provides, it’s irrespective of boundaries and space.
In other words, the cloud computing allows you to carry on computing tasks of business activities, data analysis or mining over the internet.
It’s a mutation that manipulates time and space constraint workplace. Let’s simplify what I want to convey. If I want to reset or format my mobile device, I need to transfer the pan data from its movable (memory card) and immovable memory (ROM). But, the question is ‘Where’; where should I transfer it?
Here, Google drive offers its cloud space. You can browse and trigger data migration over the internet. Subsequent to phone formatting, you can re-install that data anytime. You can heave a sigh of relief as its remotely located Google server manages your data.
The cloud computing, indeed, minimizes the memory or space constraint. Because of its vitality, security and turnaround time, many reputed industries from all domains rely on it. Instead of relying on a space-bound domain hosting, this computing delivers a frictionless paradigm to store big data and analytics.
Don’t you believe? Go through the list of these top cloud computing products that serve the cup of tea of data scientists:
· AWS Elastic Compute Cloud (35%)
· Google Compute Engine (20%)
· AWS Lambda (15%)
· Azure Virtual Machines (13%)
· Google App Engine (13%)
· Google Cloud Functions (11%)
· AWS Elastic Beanstalk (7%)
· Google Kubernetes Engine (6%)
· Azure Functions (5%)
· AWS Batch (4%)
· Azure Container Service (4%)
· IBM Cloud Virtual Servers (3%)
· IBM Cloud Foundry (3%)
· Azure Kubernetes Service (2%)
· Azure Batch (2%)
· IBM Cloud Container Registry (1%)
· IBM Kubernetes Service (1%)
· Azure Event Grid (1%)
· Amazon Web Services (40%)
· Google Cloud Platform (25%)
· Microsoft Azure (20%)
· IBM Cloud (6%)
· Alibaba Cloud (3%)
The cloud provides with immunity to store and analyze data of any size on the World Wide Web. The space and time constraints don’t appear as a roadblock. Thereby, if your data repository gets relentless inflow of sensory data, cloud is the best virtual assistant to let you analyse data without worrying about time and storage. It assists you:
Apart from these, cloud always gives a strong competition to the data science. The data scientists are aware of diverse viabilities of this computing and data science in relation to data analysis. This comparison will terminate all confusions regarding both: