Big Data Cloud Evaluation Checklist

24 Aug. 2015 Big Data

Big Data management is no longer an ‘if’ for companies, it is more a ‘when’ and ‘how’. With industry stats like 20% reduction in patient mortality by analyzing data in Healthcare & 92% reduction in processing time by analyzing call and networking data in the Telecom industry, enterprises are achieving Big ROI with Big data.

Handling big data on the cloud seems to be a viable option for enterprises looking for a scalable and cost optimal alternative. However, organizations need to ensure they understand the relationship between big data and cloud computing before moving their content to the cloud. This article throws light on connection between the two and presents a set of criteria you can use before adopting a cloud saas solution.

Big Data and Cloud Computing

Big Data in Cloud Computing

What is Big Data in Cloud Computing?

Cloud-based Big Data Solutions help businesses manage customer loyalty by sending an online coupon of a favorite store to the customer. The combination of cloud with big data enables users to easily access computing and storage resources with little or no IT support. It also minimizes expenses occurred on hardware or software for maintaining the ecosystem. In addition, important business decisions can be made regarding quality management of a product in a plant through collection and analysis of data gathered from various sensors.

A cloud-based service can provide an economical solution to your big data needs, but it has its own challenges. Therefore, it is necessary to do your homework before moving big data onto the cloud. Given below is a cloud computing checklist that you can use to evaluate your options before developing your big data and cloud infrastructure:

  1. Data integrity: You need to make sure that your cloud provider has the right controls in place to ensure the integrity of your data.
  2. Compliance: Make sure that your cloud provider follows the required compliance issues specific to your company or industry.
  3. Costs: Costs tend to multiply when you are implementing any change. Be careful to read the fine print of any contract, and make sure you know what you want to do in the cloud.
  4. Data transport: Be sure to figure out how you get your data onto the cloud in the first place. For example, some providers will let you mail it to them on media. Others insist on uploading it over the network.
  5. Performance: As you’re interested in getting performance from your service provider, make sure that explicit definitions of service-level agreements exist for availability, support, and performance. For example, your provider may allow you to access your data 99.999 percent of the time; however, does this uptime include scheduled maintenance? You need to check the contract.
  6. Secured data access: What security controls are in place to make sure that you and only you can access your data? In other words, you need to check what type of secure access controls are in place? Do they provide identity management? You need to ensure that access to computer resources, applications, data, and services is controlled properly.
  7. Location: Where will your data be located? In some companies and countries, regulatory issues prevent data from being stored or processed on machines in a different country.

One of the key characteristics of big data on cloud is scalability: Users can add or subtract resources in almost real time based on the enterprise’s changing requirements.

Are you looking for a custom big data development partner? Or need scalability in your business application?

Rishabh Software can be your technology partner to help you develop big data solutions for your business. Our quality delivery services will ensure YOU implement a Big Data strategy that best suits your enterprise needs.

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