Data analytics vs data science: what’s the difference?

The data analytic industry has grown at an astronomical rate in recent years. Large and small businesses alike are flooded with data and information, so it should come as little surprise that the big data sector has expanded at an exponential rate over the last decade.

Data science is a field that allows businesses to develop and implement data-driven, customer-centric strategies based on real-world information and statistics. Data analysts, on the other hand, will concentrate on developing ways of gathering, processing and organising data in order to find actionable insights for current challenges and queries.

So what is data science? And what is the difference between data science and data analytics? 

What is data science?

Data science encompasses an array of innovative analytical solutions. A field combining a multitude of skills and knowledge, data science is the extraction of meaningful insights from data, statistics and information. Data scientists utilise machine learning and artificial intelligence (AI) to generate data insights which can be translated into tangible value for large and small businesses alike.

Data science has become an increasingly important sector in recent years. This is because in the age of big data, businesses and organisations are looking to gain a competitive edge over other companies. With data science now such an enormous industry, businesses must get on board or risk getting left behind in the rat race.

The term data science encompasses a number of data-centric solutions in the sector, including data analytics, data mining, machine learning and several other similar services. However, although data science and data analytics are often used interchangeably, the two terms are not the same.

What is data analytics?

Data analytics is the act of obtaining and analysing data in order to make data-driven decisions. Contrary to popular belief, data analytics is more than merely collecting and analysing numbers. It the identifications of emerging patterns and trends in order to reach data-driven conclusions.

When it comes to modern business operations data analytics is incredibly advantageous, especially when it comes to marketing. Data analytics is usually offered by data analytic companies who, on behalf of businesses and organisations, use emerging trends and patterns to create forward-thinking, data-driven strategies, campaigns and decisions.

Data analytic companies

As the name suggests, a data analytic company exists to analyse data. The purpose of a data analysis company is to unearth data before analysing emerging patterns and trends. Data analytic services are typically completed on behalf of a customer, such as an organisation or business, who are looking to improve the effectiveness of their own initiatives and campaigns. From historical data to real-time analytics, there is a variety of data types that can be analysed.

Using cutting-edge technology, data analytic companies use data analytics, data reporting and business intelligence tools to find actionable information to their clients. This data reveals crucial insights and performance indicators to both large and small organisations, allowing them to identify patterns in client behaviour and streamline specific tactics and campaigns.

So what other services will a data analytic company provide? 

Data visualisation

By utilising data visualisation tools, large and small businesses alike can easily translate their collected data and statistics into easily accessible graphs, charts and other interactive visualisations. Data visualisation can assist in predicting future patterns and highlight trends affecting a business or organisation. 

Data replication

As the name suggests, data replication is the act of replicating and copying data, which is then kept in a physical warehouse or on a cloud-based server. Businesses and organisations will duplicate their data and information to make it more accessible to both employees and others outside of their operations. The service can also be used to back up essential data and information in preparation for developing a proactive disaster recovery strategy. 

What is the difference between data analytics and data science?

Although the terms data science and data analytics are frequently used interchangeably, the two professions are fundamentally distinct. Data science is an all-encompassing term that refers to a variety of analytical and transformative services, whereas data analytics is a more specialised solution falling under the data science umbrella. 

In contrast, data analysts will focus on establishing methods of acquiring, processing and organising data in order to uncover actionable insights for current issues and conundrums. Simply put, data analytics is concerned with finding solutions to problems for which we do not have answers.

The techniques in which both phrases analyse data are a useful way to tell the difference. Data science is a broader term that refers to the process of sifting through enormous amounts of data in search of patterns and insights. Data analytics is more precise and will look for answers to specific problems. In essence, the two fields are two sides of the same coin. Although the two services are closely related and frequently overlap, data science and data analytics are not the same. 

Final thoughts

There is no denying that modern businesses and organisations are inundated with data and information in today’s fast-paced world. As a result, it should come as no surprise that the data science consulting sector has grown at an exponential rate over the last decade.

Data science is a tool that allows large and small organisations alike to build and implement data-driven, customer-centric strategies based on real information and statistics. Data analytics, on the other hand, is a type of data science that concentrates on developing ways of gathering and organising data for the purpose of finding actionable insights for current business challenges.

Of course, data is useless without the knowledge and experience of analytics and transformation industry analysts and scientists. As a result, modern businesses are increasingly turning to data science and analytic services to help them realise the full value of their data. Over the last two decades, it has been increasingly clear how essential the sector is. Innovative and forward-thinking, data science holds significant value for modern businesses.

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