Today’s businesses are reinventing themselves with Artificial intelligence capabilities, be it chatbot or robotic process automation.  The increase in AI-enabled services are also creating higher demand for high-performance computing to process large gigabytes of data. This has also led to Big data processing using cloud environments.  Virtual assistants like Alexa, Google Assistant, and more have brought cloud, analytics, and AI a connected experience in our daily lives. 

Market Size:

According to Infotronic, the Cloud Computing Service industry is predicted to reach a revenue of $150 billion by 2020. They also predict that 83% of enterprise workloads are going to be on the cloud by this year without considering the pandemic and how it has now forced many companies to move to cloud solutions. Data analytics in the cloud will help your business be a part of the 90% of companies that use the cloud in some or the other form.

What is cloud computing?

Simply put Cloud Computing is like renting a house instead of buying a house. You pay for the time you stay without having to have the additional responsibilities of maintenance and up-gradation. Without physically downloading the software you can use the internet to remotely access everything.  Everything you need is located across multiple data centers having dedicated servers, data warehouses, and multiple backup data centers to make sure your data is safe.

Essentially there are 3 types of cloud deployment

• Private cloud: A private cloud is a cloud environment dedicated to one organization.

• Public cloud: A public cloud is a service shared by multiple organizations using “multi-tenancy”, where virtual machines are used for renting the same server space among multiple tenants.

• Hybrid cloud: They are a combination of public and private clouds. In Hybrid clouds, companies use a private cloud for some confidential services and public cloud for other services.

Cloud computing can be categories into 4 types:  

• Infrastructure as a Service (IaaS) – where you can rent out the entire virtual infrastructure like servers and data storage spaces;

• Platform as a Service (PaaS) – where you can rent platforms to build your own applications;

• Software as a Service (SaaS) – where you as a business can access developed applications that run on the cloud and

• Data as a Service (DaaS) – where your entire business data is on the cloud available for remote access

Can we analyze data without the cloud?

Advances in big data and cloud computing have developed these technologies to complement each other. While data analytics interprets huge data into meaningful insights, cloud computing makes this process light and convenient. But can they work without each other? Let’s consider how your data analytics platform would work without cloud computing. Your business will need to purchase computing infrastructure to handle the huge amount of data processing. You will need a system with high processing speed and huge storage capacity. This system will need access to servers, bandwidth, power, and cooling. It will be similar to the time you installed heavy gaming software by clearing out your favorite vacation photos.

Once you have found the system that can handle this you will need to purchase a robust analytics application. You will need to install, configure, and run the application in this system and feed it with all the data of your business. It will process this data and give you meaningful insights.

Need a change? The application will need to be modified and deployed to reflect the change. You will probably rethink every change you need. Even with all this, sharing insights becomes complicated. Let’s not forget the dependency on the system in use. These traditional systems require huge investments and always fear the test of time. With technology changing every fortnight it takes a huge commitment to be using outdated systems simply to justify the money and vision invested in them.

Data analytics in the cloud will reduce your dependency on the desktop. The big data cloud architecture will handle all the processing of the data at a remote server. By using aggregators and integrators, the client’s data sources are integrated into data warehouses that use SQL, Hadoop, Hibase, MongoDB, DynamoDB, and other such data management frameworks. This is then passed through a cloud-based analytical engine that interprets this data followed by a reporting engine that uses data visualization to bring you what you need. This will clear up the processing space of your system. 

You will have remote access to the entire data computing library that is integrated easily with your existing system. What happens when you request a change? It is simply built and integrated directly to the cloud, reducing your deployment time while you continue to access your daily reports uninterrupted. Sharing these insights becomes convenient with SaaS Dashboards. You simply sign in through your preferred browser, view the reports, export them into the format you prefer, and share them. Everyone who has access to the data cloud is connected and on the same page. It bridges the dependency of your local desktop environment by transporting everything to the cloud.

Check out our exclusive interview with Google tech sales specialist and a startup mentor, Mr. K C Ayyagari to gain insights on cloud technology and its role in the analytical transformation.

What is big data’s relationship to the cloud?

Big data management forecast- Courtesy Forrester

A Forrester Research survey in 2017 said that big data solutions via cloud subscriptions will increase about 7.5 times faster than hosted desktop options. Let us consider a cloud-based analytics system. According to comparethecloud.net, “The SaaS Dashboard concept is a way in which to present a cloud-hosted application suite to a user without the need to use a hosted desktop interface.”

Big data impacts and benefits using cloud computing

1. Just a click away

Having everything at your fingertips means that you don’t need to depend on anyone. Besides having all your data insights readily at your fingertips, cloud services are on demand. You can choose how long you want the service and pay only what you use.

2. Easily shareable

Do you need
your sales team to know that they need to up their efforts to meet targets? Simply export the dashboard reports or let your managers view the SaaS dashboard.

3. Integrated

You can easily have all your applications work easily with each other through cloud-based analytics.

4. Never lose your data

All your data is backed up all the time on remote servers and data warehouses. You save a lot of storage space by simply putting everything on the cloud.

5. Fast and lightweight

Do you want to change the way your data looks? Need your data insights designed specifically for your system? Cloud-based analytics reduces deployment time required to generate reports and helps you control your data anytime.

Big data processing in cloud computing environments helps you rent access to software without creating a hole in your pocket. At geniSIGHTS, we understand big data implementation costs and how resource sharing still needs a personalized design for your business needs. With FLASH, our AI-powered dashboard that gives you data analytics in cloud environments (or on-premises), you will never have to worry about anything but your business. Using the cloud has made FLASH highly customizable to fit your business needs. You can simply integrate it into your existing systems. It’s AI-based data insights that use machine learning to adapt based on your decisions. Learning from you as you learn from it. Conversational AI-powered voice control reports that are lightweight and easily shareable through the cloud.

Check out our AI-driven intelligent solution, FLASH, on our website: https://flash.genisights.com/

#AI #ArtificialIntelligence #IoT #bigdata #machinelearning #analytics #datascience #cybersecurity #deeplearning  #EmergingTech #Robotics #chatbots #CloudComputing #SelfDrivingCars #finserv #ArtificialIntelligence #iiot #ML #4IR #AI #ML #CustomerExperience #CX #Chatbots #VirtualAssistant #VirtualAssistants #Omnichannel #Tech #Blockchain #businessanalytics  #analytics #techthatmatters #data #datascientist #datascience