5 tips for turning big data into a valuable asset

Few companies have so far taken the plunge and rolled out big data projects that truly drive business advantage

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'Big data’s time will come, it isn’t going away'

 

Big data has been a hot IT topic for years now and interest continues to ramp up. Yet, much of the talk has been hype.

The truth is, organisations understand the concept of making better use of their information assets to drive competitive edge and they appreciate the huge potential of the market to grow rapidly in the future. Yet, they often struggle to build their own big data environment. They can see they have data resources that could benefit them, if properly harnessed, but they don’t know how to take advantage.

Today, businesses want to hear less about potential benefits and more about putting a clear structured transition path in place. Here are five tips for building a big data environment that delivers real business value.

>See also: Analyse this: Big data

1. Make sure you’ve got processing power in place 

Before you even start your big data project, you need to make sure you have the capability in place to manage it effectively. Whether we are talking about transactional application servers, specialist appliances for applications such as business intelligence, or the supercomputers used for digital simulation you need to have significant amounts of processing power at your disposal, simply to deal with the vast volumes of data typically processed in big data implementations.

But that’s not all. Such systems are increasingly seen as business critical and therefore they have to prove their total reliability and, given the weight of economic and environmental issues, their ability to offer optimum energy efficiency. 

2. Start with storage

To build a successful big data environment you need to start with the foundations. Implementing a robust storage infrastructure is the crucial first step. To ensure service levels are aligned with business needs, make sure systems are scalable and easy to access.

Here, the latest scale-out storage solutions can help, in processing large and complex data sets whilst minimising operational management, permitting quick access to data and providing the flexibility to increase capacity in a linear fashion.

>See also: The risks of ignoring big data

3. Build in analytics and business intelligence

Once you’ve put the storage solution in place, you can start to use data as a strategic tool by implementing the necessary storage analytics to evaluate and gain useful insight from it. You can then deliver applications like business intelligence (BI) that allow you to extract optimum business value from your data. 

Modern BI provides a querying environment built to conduct advanced analytics to transform data into knowledge; its entire structure and mission are different from a traditional transactional environment. As such it is ideally suited to its new role as an enabling technology capable of helping businesses to exploit their big data environments. With corporate data made visible in business terms, the analytics can then be enhanced to incorporate external streams of unstructured data and social media to monitor competitive intelligence and customer sentiment.

The valuable intelligence that BI coupled with big data can unlock within your business has the potential to drive profitability and competitive advantage through the added level of understanding and forecasting generated. 

4. Keep systems secure

Security will be a top priority for any business putting place a big data environment. When you gather data in one place for analytics, business intelligence and strategic insight, you make it more vulnerable to attack. And the sheer size of the dataset in most big data implementations makes deploying security applications a complex undertaking.

Typically, the key here is careful planning. You need to ensure you plan ahead and put security controls in place before the dataset grows too large.  

>See also: The failures of big data

5. Choose the right partner

Unless you are a large business with a particularly strong internal big data skillset, it’s unlikely that you will have the resources or in-house expertise to capitalise on big data unaided. But you need to be cautious in choosing a partner. Big data is not a reseller-based skill that is transactional in nature. Instead, you should look to a service partner and work alongside integrators with expertise in mission-critical applications, large solutions implementations and high performance computing functionality.    
 

Future Prospects

Today, the hype around big data continues to overshadow the reality with many businesses yet to implement the technology, and others still running trials. Yet big data’s time will come, it isn’t going away. Organisations increasingly understand there is great value locked inside their data and they want to exploit it to make informed business decisions. The tipping point for big data is not too far away. To capitalise fully businesses should build on the above advice.   

 

Sourced from Andrew Carr, CEO UK and Ireland at Bull Information Systems