How is automation transforming analytics?

Brought to you by the Villanova School of Business

Analytics has been a transformative force across a broad range of industries, drawing on big data and advanced algorithms to reveal vital insights that fuel strategic planning. Many companies are also embracing the possibilities for greater efficiency and savings through automation. Bringing these technological trends together represents a major step forward in how organizations gather information and use the findings to move toward their goals.

As progress in artificial intelligence and predictive analytics opens up new possibilities for businesses to leverage data, knowledgeable experts will be essential to making automated analytics initiatives a reality. Professionals with an education that allows them to turn quantitative information into actionable intelligence will be essential to garnering the best results from these processes. Earning a business analytics master’s degree offers professionals the skills they need to work with data models sophisticated enough to solve problems.

When automation meets analytics

Organizations are increasingly relying on robust data for everything from managing fulfillment to improving customer service. To maximize their agility and responsiveness, companies need real-time insights into the information their systems collect on a daily basis. Automating analytics is a means to speed up the processes of gathering relevant data, finding meaningful patterns and acting accordingly.

This focus on automation is an important departure from the other forms of analytics that have been widely adopted. Descriptive analytics reports on developments that have already happened, while predictive analytics uses models to extrapolate what may happen in the months ahead, and prescriptive analytics makes specific recommendations to users. Automated analytics, however, carries these approaches farther by allowing a system to take action without human intervention.

Organizations will be able to apply automation in a variety of ways, streamlining their data strategies and achieving improved outcomes for customers. These types of systems are finding applications like changing prices based on demand, guiding self-driving cars, directing consumers to the marketing content best suited to their interests, and offering medical professionals recommendations to minimize risk for patients. Automation has a vital role to play in the future of data science, and organizations are still discovering its full impact.

Working with the new generation of data models

Automated systems do not diminish the importance of human data experts. Systems architects and data scientists remain essential to putting effective data management strategies into place, keeping them running efficiently and using their findings to plot what’s ahead for businesses. The Bureau of Labor Statistics predicted a 10-year growth rate of 30 percent in roles for operations research analysts, tasked with using analytics to solve problems and improve organizational decision-making.

With the right skills and tools, analytics experts can play a vital role in helping companies to capture the potential of powerful systems. Building the next generation of models and algorithms will call for striking the right balance between speedy automation and informed direction from users.

These professionals could also have growing opportunities to guide a company as a whole. Bringing together data and sound business strategy will only become a more vital part of how organizations operate. These changes are opening up leadership roles for individuals who can apply the numbers to real-world questions, and also communicate their ideas in a clear, convincing way to decision-makers.

Gaining an education in the latest analytics methods

Analytics is defining the future of business, and automation is one important way organizations will make use of their massive stores of data. For professionals who wish to thrive in the next generation of big-data-driven strategy, it’s essential to seek an education in the current thinking on analytics and the tools to apply it. Working toward a master’s in data analytics is a way to gain the necessary skills and experience in taking on real-world problems.

Villanova School of Business equips graduates with thorough knowledge of cutting-edge tools, and brings them the chance to learn from analytics experts. By studying analytical methods for optimization and simulation along with enterprise data management and business intelligence, they’ll find out how to get exceptional results from gathering and manipulating quantitative information. Visit the program page to find out more and learn how you can apply.

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Sources:

https://blogs.wsj.com/cio/2015/01/14/the-rise-of-automated-analytics/

https://www.accenture.com/us-en/insight-improved-automated-analytics

https://upside.tdwi.org/articles/2016/10/31/what-automation-means-for-data-scientist-future.aspx

http://www.datasciencecentral.com/profiles/blogs/automated-predictive-analytics-what-could-possibly-go-wrong

http://www.predictiveanalyticsworld.com/patimes/automated-analytics-can-fill-in-for-data-scientists0903152/6234/

https://www.bls.gov/ooh/math/operations-research-analysts.htm