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  • Big Data & Technology
  • Ryan Ayers
  • SEP 18, 2018

Why Writing Skills Matters When Analyzing Big Data

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Newly minted big data specialists might believe that their profession is only about numbers. Contrary to this belief, they also need business acumen, knowledge of the industry for which they’re employed in and, yes, data-centered skills, to create a data driven culture. Data scientists must also have the ability to work with and understand key performance indicators (KPIs). Today, data scientists must possess a comprehensive understanding of business objectives that drive profit and growth as well as the ability to apply this knowledge toward helping enterprises reach their goals.

Enterprise leaders need big data specialists who are creative, can collaborate with others, are skilled in research and possess exceptional writing skills. For example, research from 2016 showed varying, but growing, demand for different data science skill sets: 

  • Data analysis demand grew 54-percent
  • Data science demand grew 40-percent
  • Quantitative data analysis demand grew 38-percent
  • Data visualization demand grew 31-percent
  • Data engineering demand grew 28-percent
  • A/B testing demand grew 22-percent
  • Machine learning demand grew 17-percent

Today, the demand for data-centered skills is growing even more. As the world’s consumers and enterprises produce a constantly expanding body of digital information, the need to analyze and use it meaningfully increases in tandem.

 Writing Skills Tie It All Together

Research shows that an average of 22-percent of employers value writing skills. However, this number jumps to 27-percent when it comes to big data specialists. Furthermore, an average of 10-percent of employers demand research skills across all professions, but 29-percent want their big data experts to have this capability, and researchers have found similar correlations in the demand posed by employers for problem-solving and collaboration skills among big data job candidates.

It's vital that analysts produce reports that stakeholders can easily understand; today's captains of industry want information specialists who can present information and develop impactful content in a way that others can comprehend. Resultantly, enterprise leaders are increasingly searching for marketers and big data specialists with exceptional writing, interpersonal and written communication skills. This includes creating data visuals and other reports. By quickly and effectively communicating the results of big data analyses to team members and key decision-makers, information specialists help stakeholders to quickly grasp mission critical concepts and potentially beneficial insights.

How Data Is Reshaping Organizations

An increasing number of ambitious nonprofit leaders are using big data technology to plan and execute performance management initiatives. These passionate civic leaders are committed to optimizing organizational performance so that they can deliver the best possible community outcomes. They face challenges specific to the nature of charity work, such as high employee turnover, changing organizational objectives, expectations of meeting unrealistic goals and - of course - fundraising. In addition, they must promote the effective collaboration of large groups to make the most of internal organizational analyses developed using big data systems.

Team collaboration provides nonprofit leaders with a wider spectrum of beneficial perspectives. However, performance analysis and management is necessary to achieve desired outcomes and harness the full potential of large groups of volunteers and staff members.

Compared to other technology professions, data science is a relatively new discipline. Regardless, the time when information specialists can secure employment solely with their technical acumen has passed. This idea is outdated.  As the field matures, more information specialists are recognizing that they must deliver reports in a structured and coherent written format because stakeholders are likely to quietly discard overly technical presentations.

The Real Purpose of Data Science

Big data technology is an empowering resource. However, the reports generated by information specialists hold no value if no one can understand them. Seasoned information experts, or specialists who prefer working with the technology behind big data, may feel tempted to lean on numbers for reporting. However, they're missing the point. The most important part of a big data project is translating complex information so that stakeholders can leverage the results. Other information veterans may feel that composing an easy to understand, concise synopsis is not part of the data science process. Nevertheless, today's information specialists must embrace the new paradigm of written communication.

Data scientists create comprehensive and meaningful reports and are a valued organizational resource. However, successful data projects don't revolve around code – they’re about people.

Businesses operate in cycles. Enterprise leaders go about fulfilling their daily responsibilities, monitoring and evaluating organizational progress, coming up with new ideas – then, they do it all again. As this process continues its cycle and the business landscape continues to evolve, the role of written communication for big data projects will remain a mission-critical asset.

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