Data science is the multidisciplinary field that focuses on finding actionable information in large, raw or structured data sets to identify patterns and uncover other insights. The field primarily seeks to discover answers for areas that are unknown and unexpected.
Data science is more concerned with establishing questions to ask based on existing data than immediately applicable BI insights, preferring to locate potential trends and new avenues of exploration instead of immediately actionable answers.
In practice, data science analytics explores large amounts of raw data seeking possible patterns that may lead to more concrete questions, looking for correlations or connections in disparate datasets and even exploring better ways to find solutions for problems that haven’t even been considered yet.
In more modern settings, data science forms the backbone of machine learning algorithms, as it creates clear processes for systems to analyze and process information.
To successfully evaluate big data sets, data scientists use a variety of tools from fields including computer science, predictive analytics, statistics, and artificial intelligence.
Essentially, data science is about discovery in a broad sense, with a focus on macro-level insights that can lead to more targeted and narrowed queries for analytics. This can include both scrubbing datasets into usable sizes, or simply finding interesting clusters of potentially connected dots.
What Can I Do With Data Science Analytics?
Data science is becoming an essential field as companies produce larger and more diverse datasets. For most enterprises, the data discovery process begins with data scientists diving through massive sets while seeking strategies to focus them and provide better insights for analysis.
One of the biggest fields where data analytics software incorporates data science is in internet search and recommendation engines. Companies like Google use data science and analytics to predict search values based on inputs, recommendations, and even recognition of images, video, and audio.
In retail, data science can simplify the process of targeting by improving the discovery part of the analysis and uncovering connections that are not readily visible, leading to better targeting and marketing efforts.
See it in action:
Other industries that benefit from data science include insurance and banking, where the field helps with processes like risk management, forecasting, fraud detection, and anomaly detection.
At its core, data science is about taking large, unstructured groups of data and finding order in the chaos.