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The four key ingredients to a successful Big Data implementation

Have you heard of the Big Data dilemma? It’s a problem for many companies. It comes in two forms, both of which are ringing alarm bells for CDOs and CIOs as the competition begins to get serious about dominating market share.

In scenario one, the dilemma is that when it comes to Big Data, many companies don’t know where to start, or how to manage the complex, multi-phased Big Data programmes. Scenario two is that a company has a Big Data programme in place, but it is not aligned with strategic business initiatives and is therefore not delivering expected outcomes and ROI.

In either scenario, the result is the same: companies are not gaining the immediate insights into data that will allow them to get ahead of competitors. One thing we see in both scenarios is a common misconception: good technology on its own is not enough to a successful Big Data implementation. Whether you’re new to Big Data, or you initiated a programme some time ago, take a look at the four key ingredients we’ve found that are helping companies gain the competitive edge.

Assessing internal Big Data capability

We’ve already established that excellent Big Data technology on its own is not enough to create a winning Big Data strategy and programme, but it’s the stage that most companies seem to stop at when it comes to assessment. The problem with limiting assessment to the technology stack is that companies don’t stop to consider whether the technology is aligned with the Big Data associated business goals and whether there is underlying technical infrastructure to support it, as well as skilled key stakeholders who believe in it and who will own it.

By nature, this assessment gap is most apparent in companies that have already attempted to put a Big Data programme in place. These organisations can benefit from standing back and assessing what the original business goals are before moving to assess the operational, business and governance perspectives of Big Data. Once this is done, they can begin the process of selecting the Big Data solutions that will help meet their enterprise objectives and goals.

Creating a data-driven culture

Effective Big Data governance is a key ingredient to Big Data programme success, but creating and maintaining a data-driven culture is equally important. There is no point in bringing in Big Data experts into a business that doesn’t have data-driven culture and mindset -- or infrastructure where it is accessible as and when required.

When it comes to developing this mindset and sharing the data with the right stakeholders, companies must work together to ensure they understand and agree on what they expect Big Data to do for them exactly, and whether any business processes need to be adapted to support achieving these goals.

When it comes to building a data-driven culture, it helps to focus all key stakeholders on building a programme that is use case and business objective led, not technology led. Chances are everyone will be interested in contributing to the use cases, while not everyone will get involved in the actual technology selection. It’s a valuable step to driving a culture that will support your Big Data goals.

Choosing the right Big Data tools

Now comes the fun part: shopping for technology. The Big Data technology market is hot – there are new solutions emerging every day that are helping organisations gain insight faster than ever before. However, due to the sheer number of new technologies and the problematic legacy architectures companies now struggle to choose the best-suited option that integrates with the existing infrastructure.

Before putting new tools to the test, it’s best to assess where you sit technology-wise.
The reality is, not many organisations have the luxury of starting with a blank slate. The existing architecture may be bolted onto legacy software/hardware, and existing technologies may not be suitable for Big Data success. As difficult as it may be, some underlying technologies may have to be replaced or additional functionality built to support the new Big Data solutions.

A final few technology notes: make sure the solutions you choose have long lives. There are some excellent solutions out there that may seem perfect because they tick every box. But ask yourself, are they from small players who may not be in it for the long run? Beyond that, make sure you consider open source carefully: if it’s not widely adopted, approach with caution. Lastly, always consider the cloud – it may be more suitable for your strategy than you think.

Dilemma-free delivery

Big Data has got to deliver, it’s that simple. Given Big Data is likely one of the most significant investments a company will ever make, it’s important not only to show value quickly but also to show how that value is building.

Organisations can make this delivery easier by structuring their Big Data programmes in a way that will deliver short-term value very quickly. The value should be an actual business value rather than technical functionality working well – business leaders want to see £££s, not Terabytes.

Beginning your Big Data journey may feel like one of the most challenging obstacles your business has ever had to face, but it is well worth the effort. If you put the key ingredients in place, the insights you’ll uncover could be the beginning of a revolutionary new product or service generating growth in the future. One final word of advice: keep pushing your Big Data programme – the investment may be large, but the sky is the limit.

Mike Merritt-Holmes, Co-Founder at Big Data Partnership

Image Credit: Maksim Kabakou/Shutterstock