Data science is exploding in the data-driven world we live in. In concert, data analysis and business intelligence have grown in both value and reach. With the rising volume and complexity of data, and growth of data input technologies, data science came at an essential time to provide some methods to the expansive data volumes overcoming many modern enterprises. This interesting information came to us from DATAVERSITY in their article, “Data Science vs. Business Intelligence.”
What exactly is the difference between data science and business intelligence? It is important to begin with some basic definitions of the two terms. Data science, as used in business, is intrinsically data-driven, where many interdisciplinary sciences are applied together to extract meaning and insights from available business data, which is typically large and complex. Business intelligence helps monitor the current state of business data to understand the historical performance of a business.
Both data science and business intelligence focus on data with the goal to provide favorable outcomes. Both these fields have the capability for interpreting data and usually engage technical experts who translate or transform data-enriched results into friendly insights or competitive intelligence.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.