Project Description

Big Data storage has become a commodity business

Now that we’ve covered ‘What is Big Data’ and ‘the different types of Big Data’ in our previous articles, it’s time to get a little deeper. Don’t worry, we won’t get into the hard technical stuff, but we will give you a greater understanding of how enterprises handle large scale (big) data storage.

The next step in the big data solutions framework is understanding big data storage methods on an enterprise level. This means being able to store and manage virtually unbounded volumes of data.

As a result of current and future data storage technologies, big data storage has become a commodity business. Companies like Google and Amazon have gigantic data storage centres that are able to store and process data with minimal latency to handle their massive user bases. All of this means that your traditional USB-stick or external hard drive is not going to cut it when talking about Big Data.

Despite the advancements that improve the performance and scalability of storage technologies, there is still significant space for improvement. The potential for big data storage technologies can pose many benefits for using and further developing the technology.

Advanced data storage capabilities have the potential to transform businesses, organisations and societies across every industry. Big data is a key enabler for advanced analytics. Valuable insights can be extracted from data that provide businesses with opportunities to benefit from better decision making, improved accuracy, revenue, amongst other things. Big data analytics results in a competitive advantage over companies who do not adopt a data driven business model.

Why do we need big data storage?

In the last century, the need for being able to store and process information has risen exponentially. Since governments started keeping better track of citizen records and documents, the need for proper data storage and processing systems became evident.

However, the introduction of the Internet-of-things and the internet has multiplied this need by a factor of a thousand. The exponential increase of data generation meant that enterprises needed to scale-up their big data capabilities, including storage.

When it comes to Big Data, it’s not just the big enterprises that have to handle it because even small businesses collect a lot of information from sources like emails, social media interactions, sales, and a variety of other sources. No matter the size of the company or what industry they are in, the data must be stored somewhere before it can be sorted and processed for analysing.

In essence, the key requirements of big data storage are that it can handle very large amounts of data and continue to scale to keep up with growth. The ideal big data storage system would allow the storage of an essentially infinite amount of data. It would be able to handle both high rates of random write and read access, have flexibility and efficiently deal with a range of different data models, support both structured and unstructured data, and only work with encrypted data for privacy protection.

Encryption and protection of data is another crucial aspect for any businesses. It can be mistaken that data is private and secure within an organisation. However, cyber-attacks and hacks happen frequently. Cybersecurity is a topic that is covered more in depth in the Cybersecurity section of the Cybiant Knowledge Centre which can be found here [LINK].

Big Data storage methods

There are currently two well-established big data storage methods:

Warehouse Storage – Similar to a warehouse for storing physical goods, a data warehouse is a large building facility which its primary function is to store and process data on an enterprise level. It is an important tool for big data analytics. These large data warehouses support the various reporting, business intelligence (BI), analytics, data mining, research, cyber monitoring, and other related activities. These warehouses are usually optimised to retain and process large amounts of data at all times while feeding them in and out through online servers where users can access their data without delay.

Data warehouse tools make it possible to manage data more efficiently as it enables being able to find, access, visualise and analyse data to make better business decisions and achieve more desirable business results. Additionally, they are built with the consideration of exponential data growth in mind. There is no risk of the warehouses being cluttered up by the increasing amount of data that is being stored.

The greatest benefit of data warehouses is the ability to translate raw data into information and insight. Data warehouses offer an effective way to support queries, analytics, reporting, as well as providing forecasts and trends based the collected data. Design and data cleansing must be supported by the right storage. Normally, data warehouses depend on large storage capacities that are robust, have lower costs, and perform well.

You might have heard of the term ‘Hadoop’ being thrown around every once in a while but still don’t know what it is, which is fine. Although it is an entire topic on its own, we’ll explain it briefly. Hadoop is a software framework meant for distributed storage and processing of big data to handle massive amounts of data and computation. Hadoop revolutionises big data analytics for enterprise storage. However, if you want to read more in-depth on Hadoop and its implications, read our article on it here.

Cloud Storage – The other method of storing massive amounts of data is cloud storage, which is something more people are familiar with. If you have ever used iCloud or Google Drive, this means you were using cloud storage to store your documents and files. With cloud storage, data and information are stored electronically online where it can be accessed from anywhere, negating the need for direct attached access to a hard drive or computer. With this approach, you can store virtually boundless amount of data online and access it where.

The cloud provides not only readily-available infrastructure, but also the ability to scale this infrastructure quickly to manage large increases in traffic or usage.

The cloud also provides easy accessibility and usability. When you want to access your data in the cloud, all you need to do is enter your credentials and you will have access. All you need is an internet connection and a device for accessing the cloud such as a mobile phone or laptop computer. Cloud storage has greatly improved productivity and efficiency of businesses as employees are able to instantaneously share, access, and edit files remotely.

In addition to the previous benefits, cloud storage is also significantly cheaper than the physical storage of data. Data warehouses consume large amounts of power, space, resources and come with more risk. However, with cloud storage, a substantial amount of cost is saved.