Data Science vs. Business Analytics

Data Science vs. Business Analytics
It is very easy to confuse data science and business analytics as synonymous terms because both deal with the gathering of data, and the use of that data to form forecasts and insights. However, both of these areas of data analysis serve very different purposes, and to have a successful business, it is important to understand the roles of both. Aviana Global has helped many businesses with analysis and growth and uses data modeling to bring clarity to a very confusing and overwhelming subject.

What are Business Analytics?

Business analytics is a much more focused subset of the data gathering and modeling structure that looks directly at factors that affect business operations. Things such as cost, profits, and wages are some of the data that would be gathered and analyzed on this side. This data is used to help decision makers and management see a clear picture of their past, present, and future business functions and the trends of a specific industry. Although this does give a business easy to digest and easy to present information on the financial wellbeing of a company, it doesn’t take into account everything that can affect a business’ bottom line. Financial statistics is a great indicator, but it is not the end all. Business analytics serves a great purpose: to provide leadership with the facts to make decisions; however, it has proven in the past that seeing the larger picture can sometimes be beneficial.

What is Data Science?

Data science deals with the more ambiguous side of data gathering, and looks at all the aspects of the data collected, even if it isn’t directly related to business. This takes into account the affect that geography, demographics, and even seasonal factors have on a company’s efficiency. This helps pinpoint exactly what is driving those trends that are analyzed with business analytics. It is very beneficial to find any connection that may exist between this data and the position of a company because it could give you a deeper insight that will make decision making much more efficient. Adding data science may cause cloudiness and misinterpretation, however, so this does add a much larger aspect to the data analysis field. Data science is like having the other teams playbook, but that still doesn’t mean you know what plays they are going to call. Aviana Global focuses on helping companies with data analysis and data modeling and can bring that expertise to your company today.

Key differences between data science and business analytics

The biggest difference is that business analytics only deals with business data, while data science takes outside factors into account as well. In business analytics, there is not much coding involved, and analysis can be done directly with the statistics at hand; however, because of the scope of science data, coding is a necessity to help find connections between the amount of data. Although both can use unstructured and structured data, business analytics deals more with structured data, and rarely uses unstructured data.

Key similarities between data science and business analytics

The biggest similarity is that both use data to analyze and project trends. Business analytics may be a more focused subset used to interpret data science, but both deal with trends, statistics, and algorithms to see the past, present, and future.

Where the Field is Headed

Data science will always be a popular use of statistics, but with the rise of machine learning and artificial intelligence, data science and business analytics may become united. With powerful machines and learning capacity, the ability to collect, analyze, and present data may all come from one spot, and bridge the gap between the two areas of statistical data analysis. Aviana Global is on the cutting edge of artificial intelligence solutions to help predict efficiency for businesses, and can use data modeling to help businesses make the right decisions for future sustainability. Give them a call today to see what options they have available for you!

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