Gone are the days when organizations invested enormously in safeguarding their database. After the arrival of cloud storage, things changed tremendously for millions of companies as it allowed them to work efficiently and minimize the costs spent on premises administration. Gradually, the concept of cloud picked up pace with changing times as more number of enterprises started to move their platforms to cloud. With cutting edge technologies entering our lives, accessing massive amounts of data became a new hindrance which led to the birth of ‘Cloud Analytics’.
With Cloud Analytics, it has become easier to access crucial data and derive insights from colossal amount of documents. However, organizations have still been hesitant to unreservedly accept the data flow and security associated with it. With several choices available with cloud (private, public, hybrid, virtual private) and cloud solutions (SaaS, PaaS, IaaS) which has certain contrasting value propositions, it has become substantial to pursue certain do’s and don’ts while adopting cloud analytics.
Why should you move to cloud and its advantages?
Cost: Since the cloud infrastructure is shared by several firms, it is cost effective.
Accessibility: It provides easy and fast access through browsers or mobile devices.
Scalability: Cloud platforms offer flexibility in terms of scaling up or down infrastructure quickly in contrast to the traditional IT procurement procedures etc.
Maintenance: Traditional storage consumes time whilst raising threats to security. With cloud analytics, it becomes seamless and easy to maintain.
Faster innovation & go to market: With flexibility and available infrastructure, it provides faster innovation to market allowing the focus to be purely on business.
Why do enterprises prefer on premise deployments rather than cloud?
Data security & compliance: Cloud is perceived to be non-secure, despite numerous security certifications and incorporating more security in data centers than host cloud. Most individual organizations may not find it economical to deploy for their infrastructure.
Different types of cloud offerings and its value proposition
Software as a Service (SaaS): Adopted for applications hosted on cloud. It is remotely managed by one or more providers.
Platform as a Service (PaaS): Implemented as a combination of OS, runtime and middleware. It provides a platform for the development world to build different cloud (SaaS) applications. It delivers a set of tools and services designed to help integrate, and deploy SaaS applications quickly and efficiently.
Infrastructure as a Service (IaaS): It incorporates the infrastructure like servers, storage, and network behind the cloud platform.
Different types of cloud deployments
Public Cloud: The Cloud Service provider owns the entire infrastructure which is available to the public and provides their resources, for e.g. applications, free storage, rental based or subscription mode for the public.
Private Cloud: A particular model of cloud computing that involves a distinct and secure cloud based environment in which only the specified client can operate.
Virtual Private Cloud also known as managed private cloud model is deployed at the service provider, which is connected to the user’s premises through a secured connection.
Most small and medium enterprises choose Software as a service (SaaS), because it reduces the cost and agility. SaaS uses the web to deliver applications which are handled by a third party vendor. Whereas platform as a service (PaaS) provides agility, scalability, limited need for expertise, lessens expenditure, easy implementation and is time efficient.
The closest to on-premise deployment in terms of data security is the virtual private cloud deployments, which is best suited for business critical applications and analytics. In a virtual private cloud, performance doesn’t get hampered despite congestion on the internet.
What to look for while adapting to Cloud solutions for Business Intelligence or Analytical Applications?
Going for cloud means all enterprise systems including database are hosted at a service provider, either managed by IT or through a managed services provider. There are some benefits to it, like having a single vendor for all infrastructures. Some drawbacks include replication, cost escalation, latency and underutilizing the potential of cloud.
Before deploying of cloud, one should consider the following:
- Whether the replication is continuous in nature?
- Is it going to be scheduled?
- Is it going to be real-time analytics?
- Availability of bandwidth
Hybrid basically means a split-mode of deployment wherein some systems are hosted as a service provider and connected by VPN. These systems can be managed by IT or through a managed services provider. This also means embracing the cloud step by step. It is extremely important to pay heed to latency and bandwidth issues across the WAN, especially since analytical applications are data intensive. Moving just the Business Intelligence (BI) application and not the data base(DB) to the cloud, could add significant latency for BI application. Additionally, there would be lot of back and forth data movement. This may look attractive as there is no data duplication and the data is not hosted on cloud. However, the moot point to consider would be, where and how to split the landscape before deploying the cloud.