The increasing amount of available data has been a game changer for organizations of all sizes. This big data streams from myriad sources, such as social media and business applications, into company networks, which companies can leverage to improve their operations.
In addition, organizations are migrating en masse to the cloud to develop better software, make use of the cloud storage benefits, and improve their IT operability. Combining big data with cloud computing is a clever strategy that can propel your organization forward. In this article, we will cover the nuts and bolts of merging big data with cloud computing.
An Introduction to Big Data and Cloud Computing
Cloud computing refers to the on-demand provision of storage, database, application and computing services via the internet. A cloud service provider, such as Amazon Web Services, Microsoft Azure or Google Public Cloud, owns and manages the network and underlying infrastructure, while the consumer uses the services through a web dashboard.
Big data is defined by Gartner as information assets of high-volume, high-velocity or high-variety, demanding cost-effective, innovative forms of information processing.
The concept of big data encopasses what are called the 5 V’s:
- Volume—this is the defining characteristic for big data
- Velocity—the speed required to process and examine those large volumes of data.
- Variety—consist in disparate types of collected data, such as structured data (databases) and unstructured data (tweets, emails, images, videos) that need to be consumed and processed.
- Veracity—big data can contain a lot of noise, therefore, it is important that the tools can sift between the poor quality data from the relevant one.
- Value—when the right information is collected and analyzed to gain functional insight.
Big data is growing daily, with over 1 billion Google searches and close to 300 billion emails sent everyday. Most of this big data is living in the cloud. Let’s see why cloud computing is a perfect match for managing big data.
Big Data and Cloud Computing – A Perfect Mix
The simplest explanation for this marriage is that since big data is so extensive, it cannot be processed through traditional database and software techniques. Cloud computing provides the space required to store the ever-growing amounts of data, scale out easily, and offer fault tolerance and availability.
With hardware virtualization, it does not matter how many petabytes of data you have, as the cloud scalable environment allows you to deploy data-intensive applications, such as business analytics, for example. Cloud computing is cost-effective, as it requires no capital expenditure—as opposed to on-premise solutions—providing affordable and easy storage of data in cloud servers.
Benefits of Big Data with Cloud Computing
Combining cloud computing with big data is a perfect match, as it offers a scalable and accommodating solution for big data and business analytics. Big data projects usually start with data storage and the application of basic analytics modules, which may soon be insufficient to extract, process and analyze large amounts of data.
This requires infrastructure upgrades, which may be implemented by adding more servers to your on-premise infrastructure. However, the rate at which the data grows can make even this new infrastructure insufficient very quickly. Putting big data in the cloud presents many advantages, among them scalability.
These are some of the other benefits of moving big data to the cloud.
Installing and running a server to work on-premises can take days, or weeks. Cloud vendors provide an infrastructure with the resources it needs almost immediately. Moreover, all analytic needs are under a single roof.
As opposed to an on-premise solution, a cloud platform expands automatically, adding storage as the data increases. Moreover, the platform reduces or increases the storage space according to the requirements of the data. All major vendors offer backup systems, such as AWS Backup, with several third-party solutions offering managed cloud backup services.
Most major cloud vendors offer cutting edge security solutions to protect the data, using threat intelligence to detect and protect their customers data from attacks. The cloud is considered more secure since it does not carry the risk of a physical attack, and it usually offers multi-region storage solutions.
4. Fast time to value
Keeping big data in the cloud increases productivity, since you can create data-driven applications using the big data analytics capabilities quickly without the need for new integrations or infrastructure.
5. Data processing
Big data platforms enable the processing of massive amounts of unstructured data, sifting and categorizing it taking just a few minutes. A cloud platform combines the unstructured data from social media, for example, with the structured data on the consumer’s detail database. Transferring data in the cloud is simple and fast, with most cloud providers giving support in the migration to the cloud of large databases.
Organizations that want to use cutting edge technology to run their operations, but are budget-conscious, may find the solution in cloud computing. Keeping a big data center running can be an expensive burden for the IT budget. With cloud computing, the pay-as-you-go pricing scheme allows the organization to pay only for the storage and computing service it actually uses.
7. Real-time analysis
Since the data is received in real time, it makes sense for the analysis to also be executed immediately. The cloud platform enables users to make use of the current data, even running predictive analysis in real time.
The Bottom Line
Cloud-based management-as-a-service enables companies to master big data, combining data, operations and analytics. Cloud computing offers organizations a cost-effective way to access and manage extremely large sets of information from disparate sources. The unique characteristics of the cloud provide agility and scalability, as well as real-time processing of data.
One of the main advantages of the cloud is that it levels the field for small companies. Before the widespread adoption of the cloud, only large companies had the infrastructure and resources to analyze and use big data. Cloud computing platforms allow small companies to store and manage their data without the hefty investment in infrastructure. Small companies can purchase a subscription to their vendor of choice and proceed to store and analyze data almost instantly.