How Cloud Computing Will Drive The Future Of Data Analytics
Cloud computing and data analytics are the present-day superheroes that can run a business solely on their shoulders. Since the introduction of cloud services in 2006, it has evolved so much, and many big players in the tech industry, like Amazon, Microsoft, IBM, Oracle, and Adobe – almost all tech giants, big and small, are offering cloud services at various levels.
Data analytics, on the other hand, is the study of statistics and is as old as pyramids, literally! Ancient Egyptians used census statistics for the building of pyramids. Statistics plays an important role for governments worldwide in the creation and classification of censuses, distribution of goods, and collection of taxes et al. Data analysis is the process of collecting data from various sources and studying it to extract useful information. With the introduction of computers, the power of computation has increased tremendously, and it helped data analysis to look deep into the data to find various answers that can be benefitted from. While cloud computing is a modern technological marvel, data analysis existed long before. Before finding out the combined power of the two, let’s look at their strengths to understand them better.
Cloud computing had given all business enterprises the option of not having to buy a cow when they need a packet of milk. The analogy may seem funny, but that was the case with all the businesses prior to the cloud. Previously, business enterprises used to spend a bomb on IT infra, most of which was used just as a backup to face any eventualities or when the situation demands. When not in use, these IT resources occupy a lot of space and waste a lot of energy in terms of the power they consume and, eventually, the money. Cloud services have eliminated all this wastage by simply offering every IT resource “as a service”. Now, businesses can buy a service and pay for what they use and need not own that IT infrastructure.
Cloud computing services are mainly of 3 types. Infrastructure as a Service, IaaS where businesses can rent infrastructure like servers, networks, virtual machines, operating systems, and storage without buying these costly entities. This way, the businesses like e-commerce platforms can make use of these services by scaling up or down depending on the demand; for example, during festive seasons, they can scale up the resources as the traffic is expected to peak, and on other occasions when the traffic is low, they can scale down the resources. This saves a ton of burden for the businesses as they need not worry about scaling their hardware and can concentrate on other important business aspects. That’s one use of cloud computing, scalability of hardware on demand!
The second category of cloud computing service is Platform as a Service, PaaS. The cloud service offers a complete development framework and deployment environment for any web application for the customers. Just like in IaaS, PaaS also includes infrastructure such as servers, networks, and storage, and in addition also includes development tools, database management services DBMS, business intelligence BI tools, and all the middleware required to build and maintain a complete web application lifecycle right from inception, build, test, deploy, manage and update! IaaS is a subset of PaaS in the sense that PaaS offers all the services of IaaS and more.
The third category of cloud computing service is Software as a Service, SaaS where a software application is hosted by the cloud provider for the end users to make good of it for a price. The software provider can either host the software application and all the related databases using its servers and resources and offer services like Microsoft Azure, or in the case of an independent software vendor, ISV can take the help of a cloud provider to host his application. These applications can typically be accessed through web browsers and can be used by both B2B and B2C users. SaaS is a superset of IaaS and PaaS.
By using any of the above-mentioned cloud computing services, a business can benefit in many ways. The first and foremost benefit of using cloud services would be a drastic cutting in IT costs. Scalability is another main advantage of using a cloud-based service. Also, since cloud services can be accessed from anywhere, businesses can longer confine their manpower to offices alone. The manpower can be scattered anywhere and can work using just an internet connection. This mobility can especially be useful for startups and small businesses where employees can work from anywhere with any device cutting significant costs on premise rent and other amenities. One of the most important benefits of hosting your data on the cloud is security. On-site data storage is as good as the hardware on which it resides and is vulnerable but when you move your data to a cloud, you can rest assured as long as your cloud provider is operational, your data is in safe hands. Cloud service providers offer data security not only from physical theft, natural disasters, and damage but also from hackers and data burglars.
The above gives you an idea of cloud services and how a business can benefit immensely from using them. Let’s move on to our next business superhero, data analytics.
Have you ever encountered a puzzle on social media where you need to find a hidden figure embedded inside an image within 30 seconds and if you find it successfully, they claim you have extraordinary IQ? You might be familiar with finding the differences between two almost identical images in magazines or perhaps you would recollect those questions from a competitive exam where you need to find the number or shape that comes next in a series of numbers or shapes. Do you know what the one thing that is required to solve these types of questions where at first, these images, shapes, and numbers appear to be very ordinary and typical is? Analytical observation!
The ability to analyze the given data and arrive at a conclusion is called analytical thinking or observation. Data analytics are used to analyze what appears to be meaningless, raw, and abstract data to discover, interpret, and communicate meaningful patterns from that data. The interpretations and patterns thus obtained can optimize a business and help perform it more efficiently by providing various insights. Since data will be huge and cannot be interpreted by humans, various techniques and processes used to interpret the data have been automated into various mechanical processes, and algorithms were designed to be used on raw data. Implementing data analytics in a business will optimize its performance in various ways, such as reducing operational costs by identifying more efficient ways of conducting business, making better decisions, finding customer behaviors, and discovering new business opportunities and trends.
In today’s digital age, every business needs data for its success, as data conveys many important things. If a business ignores the data at hand, it may miss out on some important opportunities or even worse, crash the business. Based on what type of analytics you use on the data, the same is divided into 4 major types. Descriptive analytics on data will give you a description of what happened in the past. This type of data analytics will help you look into what happened previously so that you can plan a course of action. Diagnostic analytics of data will diagnose why and how something has happened, whether good or bad. If it is good, a business can follow it, and if it is bad, a business can examine ways to prevent it. Predictive analytics predict future trends based on the current data. These predictions will help prepare a business for any big business opportunities or eventualities. Prescriptive analytics will help guide a business by offering various courses of action on how to proceed based on the given data.
All four categories of data analytics mentioned above will help a business to understand its current situation through descriptive analytics, how it got there through diagnostic analytics, where it is headed through predictive analytics, and finally, how to proceed further through prescriptive analytics. Depending on the problem you are facing in your business or trying to set the future goals of your business, you may choose all or some of the data analytics.
But to apply the various analytics, you need the raw material, which is data. The more data you analyze, the more accurate the results will be.
Now that we have understood how a business can benefit from cloud computing and data analytics, let’s look at what the combination does to a business.
There’s an ocean of data, all right! But to mine those huge volumes of data and convert it into actionable info, you need to have a powerful infrastructure in-house, more so if the data is stored on-site. Applying data analytics on such in-house stored data is a daunting task. This is where the cloud comes in. Many cloud platforms offer storage solutions so that you can move your enormous data onto the cloud.
Apart from offering cloud-based storage solutions, these cloud platforms also offer integrated cloud analytics to apply to your data. This offers various benefits to a business, the first being not having a host of infrastructure at your premises. The second big benefit is you can easily build customized reports based on the geographical location of your business branches, as the data about all these different locations is now available on the cloud. The third big advantage is the cloud analytics the cloud platform offers are much faster, more robust, and safe than the in-house ones. And lastly, the data will be safe and secure on a cloud rather than on-premise!
All these advantages of combining cloud computing with data analytics will increase the efficiency of a business by arriving at various action plans and staying ahead!
As far as the question of how cloud computing will drive the future of data analytics, it is already driving. In the future, too, we can see these two evolving superheroes shouldering many big businesses to their successes!