data analytics ICT
dynamic technologies are the most suitable for your needs. Similarly, low versus high latency technologies needs to be considered.
£ Look beyond the hype – new software frameworks, including Hadoop, whilst great technologies may not be right for you. Just because they may not be right doesn’t mean Big Data is irrelevant altogether. Consider what is best for your company’s growth before investing purely based on price or hype
£ Resources – lack of resources, especially the right resources to analyse Big Data is critical to the success or failure of the project
Big Data analytics has the potential to save companies money, grow its revenue and achieve many other objectives, across any vertical. Some of these benefits include £ Building new applications – with the collection of real-time data points on its products, resources or customers – a business can repackage that data instantaneously to optimize either customer experience or its own resource utilisation
company – the source code is not available to licensees, and customers typically license the product through a perpetual license with annul maintenance fees for support and upgrades.
By comparison open-source software and source code is freely available to use. Value-added components are sold together with support services. Cloud services are hosted in a cloud based environment outside of a customers’ data centre and are delivered over the internet. Their model is subscription based or pay as you go
£ Market adoption – to understand a technology’s adoption, in
particular, open-source products, you must consider £ The number of users £ The availability of conferences – how frequent and are they well attended
£ Local community organized events £ Online forum activity
The key aspect of the MapReduce algorithm is that if every Map and Reduce is independent of all other ongoing Maps and Reduces, then the operation can be run in parallel on different instructions and sets of data. Consequently on a large cluster of machines you can go one step further and run the Map operations on servers where the data lives. Rather than copy the data over the network to the program, you push out the program to the machines
£ Improving the effectiveness and lowering the cost of existing applications – it can help replace highly customized, expensive legacy systems with a standard solution that runs on commodity hardware whilst also reducing licensing costs through the use of open source technologies
£ Identify new sources of competitive advantage – it can enable business to act more nimbly, allowing them to adapt to changes faster than their competitors
£ Increasing customer loyalty – by increasing the amount of data shared within the company – and the speed with which it is updated – a business can more rapidly and accurately respond to customer demand
Q A
What are the issues to consider when sourcing/implementing a data analytics solution?
While many data analytics solutions are mature enough to be used for mission critical production use cases, many are still in their infancy. Accordingly, the way forward is not always clear. As businesses continue to develop their Big Data strategies, there are a number of dimensions to consider when selecting the right technology partners. These include: £ Software license models – there are three general types of license for software technologies – proprietary, open-source and cloud service, Proprietary is owned and controlled by a software
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£ Agility – this comprises three primary components – ease of use, technological flexibility and licensing freedom. A technology that is easy for users and developers to learn and understand will enable a project to get started quicker and realize value quicker. The more a technology makes it easier to change requirements on the fly will make it more adaptable to the needs of the business. Open-source products are typically easier to adopt, scale and purchase
£ Main vendor versus niche provider – as many organisations are constantly striving to standardise on fewer technologies to reduce complexity, improve their competency and make vendor relationships more productive then adopting a main vendors product may help address this initiative. However, niche technology’s may be a better fit for the project.
Q A
For example, is Hadoop the only game in town?
While Hadoop has become synonymous with Big Data for storing and analysing huge sets of information it is not the only game in town. Saying that, the open source distributed file system and computation platform has had a remarkable impact to date.
The technology provides a distributed framework, built around highly scalable clusters of commodity servers for processing, storing and managing data that fuels advanced analytics applications. The reason
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