The humungous amount of data that is currently collected and the continuous decrease of storage costs over the years thanks to cloud computing, have made analysing Big Data an attractive way of arriving at solutions. However, these technologies have posed a challenge for firms as it is difficult to manage them without proper in-house infrastructure.
Many companies are looking for ways to use Big Data analytical techniques and cloud computing in order to add value to their businesses.
From involving internally hosted data sets to traditional outsourcing services and adopting cloud-based processing solutions to using internal and external sources of data and processing, enterprises are leaving no stone unturned. The question that often arises is how Big Data and cloud technologies could be outsourced.
Research has shown that a well-managed big data and cloud can benefit companies to a large extent. But we have to see whether these new technologies can be outsourced or its implications on outsourcing are negative. This is important to reap benefits by solving the issues in hand. In this article, let us take a look at whether outsourcing or cloud computing and Big Data analytics is possible and what questions one need to ask before jumping into the bandwagon.
Read More: Understanding the Relationship between Big Data and Analytics
1. Does the provider have a strong processing and recovery infrastructure?
Big data involves collecting data from a wide range of sources available. Big data technology involves applying analytical tools and processes to the chosen data sets to check if meaningful correlations exist. Value is added when usable insights are drawn from them. This is not sufficient as the provider must have a strong processing and recovery infrastructure in case a problem arises. If one considers outsourcing of Big Data processes, it is important to assess the processing and recovery capabilities of the outsourcing vendor.
2. Are pricing/licensing metrics and counting rules clearly stated?
Big data is a key to reaping huge profits, especially when combined with cloud computing. Although the sourcing is a bit complex it can be managed. Privacy and licensing metrics must be placed on top of the priority list. The pricing/licensing metrics and counting rules must be crystal clear and any doubts regarding the same must be resolved immediately. This criterion must be looked at as a deal breaker and nothing less. Make sure that the rules are comprehensive and are stated in a matter of fact manner.
3. Are there limitations on how or where the company can use the service or the deliverables produced?
Demand for high end services like Big Data and Cloud has been on a rise in the recent times. So it becomes all the more important to check whether there are limitations on how or where the company can use the service or the deliverables produced. Agreements help the service providers in their everyday business of providing services and getting paid for them. Like every other contract the service contract must clearly state who can do what, where, when and how. Also, you as a client must be clear about where you can use the services and deliverables provided by the service providers. If there are any limitations, you might want to reconsider outsourcing to that particular agency.
4. Are there service availability and response time service levels?
Response time is the time interval between the cloud service provider and the cloud service customer based on an event. The time can vary based on customer stimulus measurements. Service availability refers to the uptime of the platform. Service availability and response time service levels must be monitored to have satisfactory gains. Thus, these two metrics can be an important factor while making decisions to outsource cloud and big data projects.
Read More: Extracting Knowledge from Big Data
Final thoughts
As we are hurtling towards a future that is more entrenched in the cloud and as we end up creating more and more data which becomes part of an increasingly large Big Data, we can choose to make the most of both the technologies by outsourcing.
Even if we do not have the infrastructure to analyse big data or engage in cloud computing, several providers offer these services for those who are interested in outsourcing. If one clearly assesses these providers and takes the necessary precautions, outsourcing cloud and big data technologies can be very profitable in the long term.
