SiteSpect Synopsis: The Changing Role of Data Analysis

It’s not news that we have more data than ever. The IoT alone generates more data than we’ve ever had access to before, not to mention the bulk of time that we spend online. But now that the novelty of data collection has worn off it’s time to question what measurable value we get from the information we have. Here’s what experts are saying.

“Why You Should Learn Big Data Skills Today,” Salon

This Salon Marketplace article sites an IDC study that predicts data volume will “double every two years until 2020.” Companies already have more data than they know what to do with and a dearth of qualified analysts. The problem then becomes what to do with all of that information once you have it. At the same time, data science as a field is shifting, meaning new opportunities for new areas of expertise.

The Takeaway: We have more data than we know what to do with, so look to for new data analytic methods and growth in the field.

“As Machine Learning Evolves, We Need to Update the Definition of ‘Data Scientist,’” Venturebeat

While statistics used to the be the key for AI project management, computation has taken over as the most important skill set. Making the most of AI means that most departments not only need more data scientists, but also that data scientists must take on new roles. The trend toward neural networks over statistical models has driven this shift. Author Bernardo Lustosa writes, “Traditionalists may insist that statisticians make the best data-science hires. But I believe that curiosity, a breadth of academic knowledge, and the willingness to engage with others in the pursuit of information are more important to the role of modern data scientist than statistical training, because neural network creation requires a focus far broader than the algorithms themselves.”

The Takeaway: As organizations move towards AI and neural networks, the skill set for data scientists will need to change.

“6 Data Analytics Trends That Will Dominate 2018,” CIO

Author Thor Olavsrud looks forward to how companies will use data in the next year. The uniting theme of each of his six trends is value. We have all of this data, how will we make it valuable? The answers range from storage and information sharing, to new management and C-level roles to oversee data, to developing specific skills and strategies for dealing with data.

The Takeaway: Start implementing data management plans that demonstrate value to your business or organization.

A Little Point of View

Chances are your organization already collects more data than it uses. Like each of these authors notes, the data itself doesn’t provide any value. Value has to come from smart analysis, efficient processing, and organization. There are tools to help with this, but the evolution of the data science career will lead the charge toward data driven business practices. We’re interested to see what the data tells us.

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