Big data is a significant force in our new digital economy. Each of our countless on-line interactions leaves behind it a trail of data. For businesses, this data trail is a potential gold mine.
Gathering up this data is a business in itself. It opens the possibility of discovering previously unnoticed patterns of consumer behaviour. These patterns can in turn be leveraged to make businesses more efficient, target the right customers and provide them with more bespoke services.
Software companies around the world know how valuable this data is. They have developed a range of business analysis platforms that can capture ever more data, ever more effectively. Integrated with a company’s own website or internal systems, these platforms can provide businesses with a wealth of information.
However, while such large volumes of data provide enormous benefits they also present a challenge. The complexity of such data sets can be so great that conventional data processing systems and techniques are not sufficient to analyse them.
This is where big data begins to drive demand for data related technology skills. Regardless of how sophisticated a business analysis platform is it cannot be programmed to understand the intricacies and requirements of individual businesses.
It is up to skilled employees to bridge this gap between the data gathered and the business that utilise it. Bridging this gap calls on a multitude of roles, acting across businesses to put big data to work.
The level of demand has been highlighted by LinkedIn through their own statistics and they expect it to continue to rise. Big data skills are among the top twenty-five skills that recruiters are hiring for in 2016 on LinkedIn. This further demonstrates the demand on a global scale.
Big data creates job demand in a number of areas that can be covered by a variety of expertise. Depending on the system, these kinds of tasks can be carried out by different specialists from Search engine and digital marketers to data analysts and data scientists. We can take a look at some of the general areas these roles might involve:
When a system is being set up, an e-commerce website for example, it is important to recognise where the opportunities lie for the collection of useful data. Economy is also important in preventing irrelevant data from being collected. Data also needs to be adequately categorised as it is collected to make analysis more efficient.
Gathered data needs to be understood. Powerful data collection platforms certainly help to sort, relate and quantify data but, however well the data is presented by a system it still requires analytical skills to make it meaningful. The data specialist can draw out key indicators and distinguish them from false positives and background noise.
Once data has been interpreted the big question becomes how to act on that information. The data specialist has to combine their understanding of the data with their understanding of the business to help develop concrete business strategies. This may come in the form of creating new sales approaches, discovering entirely new areas of a market or implementing automated features that respond intelligently as data is gathered.
Of course, the business analysis platforms that gather the data also require data specialists to be involved in their design, development, maintenance and marketing. New features are continually added and existing features are continually refined to provide a better product that offers advantages to more customers.
Depending on the area they work in a Data Specialist might have any number of different data related skills. These are just a few they might have.
Structured Query Language (SQL) is the most common way in which data in a database is stored, accessed and manipulated. It is a high level language that is relatively intuitive and easy to learn but provides for a high level of complexity and takes a long time to truly master. Data analysts with good SQL skills are highly prized.
Scripting is another important skill for data analysts and data scientists. Being able to quickly develop short but powerful scripts that take advantage of data sets and analytic platforms is vital.
Story telling is another important skill for the data specialist. A good data specialist is able to readily distil the significant results of data analysis into a concise and comprehensible narrative. If you can communicate important findings to non-technical partners in just a sentence or two you can amplify the value of the rest of your skill set.
Big data is set to continue to grow and as it grows, so will it push demand for jobs to cultivate it. Refining those data related skills is a sure way to succeed in this data driven market.
Digital Skills have developed big data modules that provide participants with the relevant skills and experience to move into a career in Big Data. Find out more:
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