Data Science

Make Sense of Your Data

Over the past decade, the digital landscape has evolved dramatically. The generation and retention of data have grown exponentially. In this day and age, businesses are turning to data science as a way of making sense out of their information.

Data science is the process of extracting value from data and information. It combines multiple modern fields including statistics, scientific methods, artificial intelligence (AI) and data analysis. Data science is about more than simply discovering and analysing your information. The process encompasses the preparation of data for analysis, including the processes of cleansing, aggregating and manipulating it. Analytics applications and data scientists can then review the results to uncover patterns and trends. That information is then passed onto businesses for the purpose of gaining insights and strategising accordingly.

At DSCallards, our consultants combine their expertise and decades of experience to successfully analyse data collected from a range of services that derive actionable insights for our clients.

Frequently Asked Questions

What is the difference between data science and business analytics?

Although often used interchangeably, data science and business analytics are not the same. Data science is the study of data and information using innovative technology, algorithms, and statistics. Business analytics is a subset of data science and is the analysis of business data for the purpose of gaining insight into emerging or existing trends.

Which are the three most used languages for data science?

The most commonly used languages in the data science sector are Python, JavaScript, and Scala. Other languages include R, SQL, and Julia.

Python – Python is the most widely used programming language in data science. Launched in 1991, it’s a dynamic, object-orientated language that supports multiple paradigms including structured, functional, and procedural programming.
JavaScript – Like Python, JavaScript is a versatile, object-orientated programming language. Capable of handling multiple tasks at once, JavaScript is useful for embedding just about anything from electronics to desktop and web applications.
Scala – Scala is a scalable and effective programming language for handling big data. Useful for large and small businesses alike, Scala supports functional, object-orientated programming as well as synchronised and concurrent processing.

What is the business intelligence part of data science?

Also known as BI, business intelligence utilises specialist technology and skills to perform a descriptive analysis of data for the purpose of making informed, data-driven decisions.

Is data science just statistics?

No, data science is not statistics. Data science is a multidisciplinary field that utilises scientific processes, methods, and systems to extract knowledge, trends, and patterns from data. In contrast to this, statistics is a field predominantly based on mathematics that seeks to collect, analyse and interpret quantitative data.