Over a million developers have joined DZone.
{{announcement.body}}
{{announcement.title}}

Big Data and Cloud Computing: Made for Each Other

DZone's Guide to

Big Data and Cloud Computing: Made for Each Other

Big data and cloud computing are a perfect combination that allows for processing huge amounts of data on a scalable platform that has the resources to analyze data.

· Big Data Zone ·
Free Resource

Hortonworks Sandbox for HDP and HDF is your chance to get started on learning, developing, testing and trying out new features. Each download comes preconfigured with interactive tutorials, sample data and developments from the Apache community.

Big data basically refers to sets of data that are large in volume and cannot be processed through traditional application software. The term big data is not new, as it has been around for a long time and there are many new concepts related to the term. Even though the concept is not new in the industry, there is a lot of confusion around the true meaning of what big data actually is. When you work on a particular principle and start collecting knowledge on it, you start generating data that will be useful for you in the future to analyze and get further insights. Before computers and the rise of the internet, transactions were recorded on paper and archive files that were fundamentally data. Today, computers allow us to save whatever data we have on spreadsheets and organize them in the most efficient way.

Cloud computing offers the best technology with a wide range of applications for various purposes in the most cost-effective way. Big data and cloud computing are a match made in heaven because there is a lot of data — and only cloud computing can provide that kind of compute power to process the data. Whatever we do almost leaves a digital trail, as we generate data whenever we are on the internet. As cloud computing is transforming IT, huge amounts of compute power are needed with the help of the internet to store and analyze this data. Cloud computing has reshaped the way computers are being used to process data. Cloud has made it very simple for data storage compared to traditional data storage. Cloud computing provides scalable resources on demand and has changed the way data is stored and processed. Cloud computing is a powerful approach to analyze data provided and has become vital in the growth of big data in multiple industries.

The full potential of what cloud computing can offer has not yet been realized due to lack of expertise. Thus, many enterprises fail to realize what can be achieved through cloud computing. Due to not implementing big data in businesses in the way it should be, organizations are not growing because they are not analyzing the data available to them. The combination of big data and cloud computing will help organizations in business analytics and will also improve their decision-making in important parts of the business.

The world can benefit from this combination and can have a huge analytics advantage to generate information that is ideal for business continuity. Let’s take a look at the opportunities organizations can achieve by combining big data and cloud computing.

Agility

Traditional systems have proved to be slower since storing data and managing it is a time-consuming and tedious process. Since the adoption of cloud by organizations, it has been providing all the resources to run multiple virtual servers in the cloud database seamlessly within a matter of minutes.

Affordability

Organizations have a budget when they wish to switch to a particular technology and in this case, cloud is a blessing because it is a top technology for those on a budget. Companies can choose the services they want according to their business and budget requirements. Applications and resources that are needed to manage big data don’t cost much and can be implemented by enterprises. Only pay for the amount of storage space you use and no additional charges will be incurred.

Data Processing

Apache Hadoop is a big data analytics platform that processes structured and unstructured data. Social media alone generates a lot of data from blogs, posts, videos, and photos, which is difficult to analyze under a single category. Cloud takes care of the rest by making the whole process easy and accessible to any enterprise.

Feasibility

Traditional solutions require extra physical servers in the cluster for maximum processing power and storage space, but the virtual nature of the cloud allows allocating resources on demand. Scaling is a great option to get the desired processing power and storage space whenever required. Big data requires a high data processing platform for analytics and there can be variations in demand that would be satisfied by only the cloud environment.

Challenges to Big Data in the Cloud Environment

  • Big data generates huge amounts of data and it is complicated to manage this amount of data on a traditional system. It is also difficult to analyze this data on the cloud platform to extract only the important bits.

  • While moving large sets of data, there is often sensitive information, like credit and debit card details and addresses, which is a major security concern.

  • Businesses face large security concerns when they have their data on the cloud. Attackers seem to come up with new ways to breach into the system, which dents a company’s reputation and leads to cloud abuse.

  • The replication of data is vital in case of an event where there are chances of losing data. Analysis of data is not possible in such case.

Conclusion

Big data and cloud computing are a perfect combination and allow for the processing of huge amounts of data on a platform that is scalable and that has the resources needed to analyze data. Obviously, there are opportunities and challenges when it comes to these two technologies — but isn’t that a part of anything in the IT field?

Hortonworks Community Connection (HCC) is an online collaboration destination for developers, DevOps, customers and partners to get answers to questions, collaborate on technical articles and share code examples from GitHub.  Join the discussion.

Topics:
big data ,cloud computing ,data analytics ,data processing

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}