Using Big Data has become one of the most important ways for big businesses to learn more about their customers, better recognise how their products and services are being used and consumed, and gain a competitive edge in their industry.
In order to harness this vast volume of data – IBM famously said that 2.5 quintillion bytes are created every day – organisations are adopting Big Data technologies. Often this takes the form of a ‘data lake’, a large scale repository designed to store vast streams of structured, unstructured and raw data, created by everything from industrial goods and smartphones to fitness devices and fridges.
The uses of Big Data are countless and we’re still at the tip of the iceberg as far as its many applications. Retailers, for example, use it to gain insight into customer buying behaviours and preferences. Leisure and travel operators can optimise services to improve satisfaction. The healthcare industry can better understand illnesses and serve patients – even politicians are using Big Data to predict voter behaviour and the outcome of elections.
Whatever an organisation plans to do with Big Data, a bigger question often remains: how do you make sense of all this data and turn it into something of genuine use to your organisation?
At this stage, many businesses turn to some of the most sought after people of the moment, with the so-called ‘sexiest job of the 21st century’: data scientists, who have the skills to dive deep into the murky sea of data and emerge with treasure.
This eBook highlights seven main challenges of data ownership, and the consequences of navigating a sensitive issue.Read this to discover:
- Why organisations need a secure and efficient data storage solution to avoid losing valuable customer data
- How to ensure your business collects, handles, processes and stores data in accordance with the law
- Why organisations should complete effective risk assessments of the data they collect and identify commercially sensitive data
Although there remains a lot of confusion about what the difference is between a ‘data analyst’ and a ‘data scientist’ (you can establish what sets them apart here), such roles share a main aim – to extract unstructured data, prepare it for use in predictive and prescriptive modelling, evaluate it and devise data-driven solutions in order to glean relevant, actionable insight. Then, importantly, explain the value of these insights to determine new opportunities and make business decisions.
Needless to say, this has made data scientists extremely desirable and allowed those with such experience to command impressive salaries. The process of data ‘wrangling’ – taming all this wild and uncultivated data and processing it into something more desirable – takes up a huge amount of a data scientist’s day and is a challenging task that only the specialised few are willing or capable to take on.
Perhaps not for long, though. Many organisations have started introducing software that is able to automate some of this behind-the-scenes data shaping, and there’s nothing to say your organisation cannot make any use of data without a data scientist on board.
Some businesses are already taking more of a self-service approach to tackle Big Data challenges like preparation, analytics, governance and data modelling. Here, any number of cloud vendors or as-a-service providers can create algorithms for serving insight and predictive recommendations for improved customer service.
It’s easy to assume that you need a PhD in Data Science before any of the mysteries of Big Data will be revealed to you. Yet even humble marketers can be empowered take on some of a data scientist’s duties thanks to sophisticated analytics, Business Intelligence and CRM software. These can offer insights on big data sets with a range of visualisations, dashboards for reporting and the ability to create queries without any programming skills.
For example, a solution like Tableau – which can be integrated with our BlueVenn marketing platform – is already being used to analyse customer spending habits, respond to website browsing behaviour trends, map geographical customer patterns and more.
Quite simply, while a high flying data whizz might be doing wonderful things for a Fortune 500 company, that’s not to say that anyone else cannot get a piece of the Big Data action. All marketers need to work on now is thinking about what questions they want to ask of it.
Big Con/Big Data eBook
Big Data projects provide a faster response to Marketing questions and enable businesses to make better informed decisions.
- Want understand how to gain key information to make better, more effective decisions
- Need more information on how to get the right product to the right customer at the right time
- Are a marketing professional looking to exploit the benefits of Big Data