How to become a part-time data scientist

Technology-driven change is impacting every business today. To keep pace with it, organisations need to be continuously adding new strings to their bow and new lines to their job descriptions.

Data is the new king – big data is no longer just a buzzword or a marketing concept, it’s a practical reality in every business. Data volumes are exploding and so are the opportunities to understand customers, create new business, and optimise existing operations.

No matter what someone’s current skillset is, if they’re not a part-time data scientist today, they soon will be.

The ability to do light data science (you don’t have to become a fully-fledged PhD-armed data guru in this new environment) will be as powerful a career tool as an MBA.

Whether someone’s in finance, sales, manufacturing or retail, unless they take on the role of part-time data scientist in addition to their other duties, they may find their career progression soon hits the buffers.

Successful companies today are data-driven.  Data literate employees that slice and dice data in order to understand the business and make timely decisions can have a positive impact on a company’s operations and its bottom line.

Analysis indicates that the adoption of big data is much more advanced in some countries than in others. As a result, different marketing messages resonate much better in certain regions.

Combine that data with web traffic activity, the impact of holiday schedules (Spain, for example, has a number of national holidays in November and early December), weather patterns and other factors, and there is a much clearer picture of how these various elements impact marketing efforts.

It’s no use simply looking at global trends or making educated guesses – businesses need to drill into campaign data on a country-by-country basis.

So employees should dive in and get dirty with data. The good news is that anyone can become data literate now without spending years studying for a post graduate qualification.

Start by becoming comfortable with Excel and pivot tables – a data summarisation tool, found in applications like spreadsheets or business intelligence software that lets you quickly summarise and analyse large amounts of data.

Learn how to group, filter and chart data in various ways to unearth and understand different patterns. Once the basics are mastered, bring new data sources into the mix – like web traffic data or social media sentiment, for instance. This data can be aggregated in much the same way as analysing basic inventory levels or discounting trends.

>See also: How companies are using data science to harness the power of the crowd

In the future, the introduction of new data visualisation tools will make working with big data far easier for an ever-expanding team of part-time data scientists.

Anyone already comfortable with spreadsheets and statistics, and with the core competence to spot different patterns in data as it is rolled up by week or by month, can spot trends using data visualisation ten times easier than trying to do it with the help of spreadsheets alone.

The people should not forget to update their job description. They’ve just joined the growing ranks of smart business users who have earned their part-time data scientist chops.


Sourced from Ashley Stirrup, Talend

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Ben Rossi

Ben was Vitesse Media's editorial director, leading content creation and editorial strategy across all Vitesse products, including its market-leading B2B and consumer magazines, websites, research and...

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