Using the Cloud for Big Data Development is a good choice. It will help the businesses to increase their operational efficiencies with a minimal initial INVESTMENT. They just have to pay only for the facilities they are using. FURTHERMORE, they can upgrade or downgrade the facilities as per the changing business requirements.

For some ENTERPRISES, DEPLOYING Big Data technologies on their premises prove to be a costly affair.  Most of the time, they do not possess the required expertise to deal with Big Data deployment. Furthermore, the initial investments in these technologies are more. Their business requirements are also changing with market conditions. The tools and technologies related to Big Data also tend to evolve with the changing requirements. So keeping updated with the latest versions/tools prove to be costly for the enterprises. So, the cloud seems to be a better alternative to start with the Big Data initiative. There are several players in the cloud space. The major Big Data Cloud providers are:

1. Amazon Web Services
2. Microsoft Azure
3. Google Cloud Platform
4. Rackspace
5. Qubole etc.

Developing a cloud-based solution for Big Data involves a lot of awareness regarding the various Big Data offerings by different cloud providers. At the very first a business should be very, very clear in its requirements regarding Big Data. These requirements can be something like:

1. Kind of insights needed
2. Data Sources
3. Storage needs
4. Processing requirements (batch/real-time) etc.

Once you are clear in your Big Data requirements and strategies for future developments, you can choose a better combination of the storage solutions, processing platforms and the analytical tools to get the required results from your Big Data initiatives.

Depending on the business constraints and the state regulations, you can decide to opt some Big Data solutions from the cloud and some tools can be employed WITHIN the enterprise to have a better tradeoff. This way you can ensure confirming the various regulations as well as make efficient use of the available resources and the budgetary provisions.

In Big Data projects, one of the greatest concerns is data availability and accessibility. The cloud providers assure 99.9 % uptime. They also employ various data checking and security mechanisms to ensure data availability all the time. Making such provisions at an enterprise-level requires heavy investments in not just capital but also in tackling the operational challenges. It is observed mostly that despite having sound planning, the demand becomes difficult to anticipate.  This results in under or over-allocation of resources which ultimately affects your investments. This will enable the new services, products and projects to initiate on a small scale basis with minimal or at very low costs. This gives a lot of room for innovations. So, opting for cloud seems to be a better choice as far as the initial journey into the world of Big Data is concerned.