The amount of data being created in the digital world has increased to such a level in the last few years that there is not, at present, enough capacity to store it all. This has put many organisations in a position where they have so much data they are struggling to manage it effectively. In this post, we’ll look at the challenges facing Big Data users and highlight some of the best data management practices that can be used.
Overview of Big Data management
Developments in technology, such as the Internet of Things, are enabling us to monitor and measure the world on an ever-increasing scale. Data is being created faster and in more volume than ever before. During 2017 it is predicted that most organisations will see a 50% growth in the amount of data they hold, with corporate data, databases and backup systems growing by over 90%. As a result, many enterprises are being forced to look at better ways to manage all the information they are collecting.
One of the problems many organisations face is spending too much time, money and effort finding effective ways to store their Big Data. The need to constantly purchase and manage extra storage is both a burden on their finances and a waste of time for IT staff who could be put to much better use working on more strategic projects. Without a more practical, long-term solution, these inefficient methods will continue to hamper the effectiveness of the whole organisation.
Challenges to managing Big Data
There are three main challenges when it comes to Big Data, these are storage, processing and data management. However, better storage systems are now available because of the development of scalable infrastructures, especially in the public cloud; and bespoke hardware has led to improvements in processing: the last big challenge that remains is to develop a workable solution for managing the data lifecycle.
Understanding how data is used
The key to developing better data management procedures lies in understanding how data is used within an organisation. In a typical organisation, much of the data that is gathered is repurposed by different departments. Each department may create their own copy of the data, process it for their own needs and then add to it with their own synthesised data.
What may start out as a single terabyte of raw data can quickly expand to 20 or 30 terabytes once every department has used it for their own purposes. The vast majority of this 20 to 30 terabytes, however, is the initial raw data duplicated many times over. For organisations using Pay-As-You-Go cloud storage or a disaster recovery site, this equates to a massive hike in storage costs.
Best practices: reducing data through virtualisation
This is obviously highly inefficient and the solution lies in being able to reduce the amount of unnecessary duplication taking place. This can be achieved by virtualising the original data so that it can be used by multiple applications across the organisation. In this way, the only additional data that needs saving is the synthesised data resulting from departmental processing.
The result of virtualisation, therefore, is a greatly reduced data footprint that is much easier to manage. It takes less time to process; it can be managed centrally, leading to better security; and because all versions of the data are visible, it ensures that analyses are more accurate.
Other benefits of virtualisation
Virtualisation also brings other benefits to organisations. It increases flexibility, reduces the financial burden and can protect users from being locked into their IT vendor. In addition, smaller but smarter Big Data is easier to backup, access and restore. And with less effort needed to manage it, it frees up IT departments to work on more critical initiatives.
Cloud and Big Data
The most cost effective way to manage Big Data is through cloud computing. Cloud provides 100% guaranteed uptime; unlimited scalability to cope with increased storage and processing requirements; and can be paid for on a Pay-As-You-Go basis so that costs can be kept to a minimum. Indeed, using a cloud provider means there is no need for capital investment in buying hardware or running your own data centre – these, together with many of the day to day IT tasks, are provided as part of the service.
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