We’ve switched our classes to live online. For more Covid-19 updates, click here

The role of Data Science culture in the application of organisational analytics

The role of Data Science culture in the application of organisational analytics

What is data science and how can it be used in a business?

Back in the early 90s, artificial intelligence seemed far-fetched. In today’s time, it is a reality. Such advanced technology has ushered the use of big data and the need for storage of such sensitive information.

For an organisation to function smoothly and make valuable decisions, this enormous amount of data needs processing. It is evident the current IT industry has had a major impact on the global corporation and market; everything revolves around data and its optimum usage. Data scientists are able to successfully process this large amount of data and have become increasingly important to corporations by helping them make informed business choices.

Read this blog to understand the role of data science and how it is an essential for organisational analytics. 

What is data science?

We areall familiar with the term data and how relevant it is in today’s age with all our information being compiled and saved on systems in different forms. Businesses handle the data of millions of customers and therefore need to assure there are no compliance issues. Effectively handling such large information with ease is one of the benefits of data science. 

The advent of the digitised and AI dominated world has made this matter increasingly interesting and complex. Data science is used to take use all this data and extract interesting findings from it.

Why we need data science? 

Traditionally, data was adapted to store structured information. However, when it comes to unstructured or semi-structured data, the old ways are of no use. Structured data is organised and can be searched in database easily, for example someone’s name or date of birth. While unstructured data which includes social media activity has a less pre-defined model; it falls somewhat in the middle as while it is easy to analyse, it cannot be placed in a regional database.

Look at how e-commerce websites make use of customer data for instance, through analysing their browsing history and activity on social media for purchasing products. This is where collection and processing of enormous amount of data come into use. Companies use effective models to synthesise the data and use is to attract a bigger customer base. This is shows the importance of data science in business. 

Another example is how data science is related to the role of AI which relies on the information that it collects to extract necessary knowledge or insights. For example, an AI dominated car would be able to drive you home by relying on data that it extracts from cameras and radars to understand its surrounding. Equipped with this information, it will know when to make a turn or overtake. 

How data science is useful for big organisations?

It is evident that every organisation relies on data and data analysis to function. Companies collect and store information or data in order to process it and make informed business decisions. 

The huge amounts of data serve little purpose without being analysed; successful businesses manipulate data to meet their needs. 

Data analytics is a tool that uses information from large data sets and helps a company make innovative decisions. This is how the inception of Amazon Fresh and Whole Foods occurred. By making use of analytics, Amazon has been able to understand customers buying preferences and how suppliers deal with grocers. This is just one of the many examples of how proper use of data science is driving business needs today. 

Role of data science in businesses?

  1. It helps in understanding the customer better
  2. Helps in improving the quality and deliverability of product and services 
  3. Improves the management of existing data
  4. Generate more revenue streams for the organisation
  5. Useful in creating a more advanced, sustainable and efficient business model 
  6. Data science analytics also work in improving internal efficiencies
  7. Compliance, risk management and governance are more efficient through big data analytics
  8. Fraud is detected, prevented and taken care of through analytics 

The role of data scientist in an organisation has become pivotal as they are the driving force behind major business decisions. Every organisation has some conceivable aims and optimum use of data science helps achieve those goals.

Businesses have to make investment decisions, set customer priorities and subsequently work on new product designs. For this they need to make use of every new technology to understand consumer behaviour. Making marketing and product decisions using data and techniques from the past is no longer a viable or constructive solution. Business leaders stay up to date with the latest technology and invest in data analytics in order to make useful marketing and product decisions.

According to Harvard, data science is the most one of the most desirable job positions in the market. If you are looking to join this growing trend then check out the Data Science for Executives programme at the London School of Business and Finance. They provide a great learning experience which combines theory and practice to effectively train you for the field.

This article is written by Nandita Kaushal and edited by Amelia Hayward-Cole.


Other News

What can business leaders learn from the COVID-19 pandemic?

The global pandemic has highlighted many heart-warming and positive stories of grit, resilience, kindness and collaboration from across the planet.…

How is COVID-19 reshaping global business education?

In just a few months, COVID-19 has changed a number of sectors including tourism, healthcare and education. Each sector is…

5 common challenges in company budgeting and budget control

All businesses benefit from having a structured approach to expenditure and resource allocation for meeting the company expenses. Proper cost…

Back to top