Data Science is a scientific process that analyzes vast amounts of structured or unstructured data, beyond what is humanly possible, to gain insight from it. Data Science may employ techniques like machine learning, predictive analysis, statistics, and others with the goal to answer a business question or hypothesis using data.

To be affective, Data Science requires creating a consolidated database and a meaningful method to understand that unstructured data. Once the data is brought together, powerful computing can be applied to the data to solve business questions. According to MIT's Computer Science and Artificial Intelligence Laboratory, a new core set-generation technique can be used to better handle big data by 'shrinking it.' MIT explains, "If you can identify a small subset of your data set that preserves its salient mathematical relationships, you may be able to perform useful analysis on it that would be prohibitively time consuming on the full set."

With such advancements continuously being made, Synechron has evaluated several business scenarios and found three of the most mature data sets and problem scenarios to be using Data Science to provide customer insights, product recommendations and to combat AML and financial fraud.

Synechron’s Data Science solutions are designed specifically to provide applications that can be applied to various scenarios which lend themselves well to a Data Science solution. Click to read how Synechron’s Data Science solutions are helping clients to automate data analysis and decision-making.

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