The data now available to companies, coupled with advanced technology and business software, enables business analysts to perform the tasks of data scientists. Individuals can gain insight into everything from sales and marketing to production or shipping delays to consumer trends by studying the data generated by a business's daily operations.
A data scientist is a professional specifically trained to manipulate and analyze data, to gain insights and create predictive models. Using a combination of data query and blending, data mining and statistics, and data visualization and presentation tools, such a professional can extract true value from your business data.
Unfortunately, the "ideal" data scientist, with advanced training, business savvy and years of experience, is like a unicorn – said to exist, but rarely seen. In practice, data scientists are hard to find, expensive, and difficult to vet for their actual skills. The good news is that advanced technology and business software provides the tools necessary for business analysts to perform the tasks of data scientists and yield effective results.
The role of a data scientist
As data analytics becomes more important to business success, companies have been looking for data scientists to supplement and simplify the work of business analysts, according to Data Science Central. The vast amounts of information pouring in from online channels, global partners, smart machines and mobile apps can offer valuable business intelligence when applied using the right analytic tools.
However, The Predictive Analytic Times explained how there is a lack of formalized training for data science in the business world. Finding a professional data scientist well-versed in the needs of a particular industry can be a difficult and expensive process.
How business analysts perform double duty
Fortunately, the availability of analytic tools has made it easier than ever for business analysts to perform the roles of data scientists. New technology can transform your data, apply data mining and machine learning, and evaluate the predictive performance of algorithms using simple point and click procedures in common business programs like Microsoft Excel.
Companies can receive the same unique intelligence they would gain from a data scientist by working with a business analyst armed with the right analytic tools. Analysts can extract real-world intelligence from digital information by combining their knowledge of the organization's processes with insights gained by analyzing modern data sources.