Business Intelligence and Data Science

Business Intelligence and Data Science

 

We live in a world where information is available to us at just a click of a button. Everything we do, say and interact with, is data for companies. This data is collected using a number of channels that we come into contact with daily, whether we know it or not. But what is all this data for? What do they do the companies or organisations do with it? 

Simply put, companies use all the data they accumulate through different means, to drive success. Dr Thomas Redman, the author of numerous articles on Data and famously known as the ‘Data doc’ said, “Where there is data smoke, there is business fire.”

We can look at the relationship between data and a company’s success like a steam train. A steam train in this analogy, is the company and the coal is the data collected. The steam train cannot function properly, or move forward without the coal, this the same in the business world. Big and small organisations use our data to gauge our likes/dislikes, trends and how we engage the world around us, to focus on those aspects and to improve their output to customers. Organisations employ a Business Intelligence Consultant (BI) or a Data scientist to analyse the data to calculate future impact on their business.

What is Business Intelligence (BI)?

Business Intelligence describes the method of analysing data to assist an organisation to make strategic business decisions and communicate the state of a business or organisation. BI allows people to examine the data and gain an understanding of trends and an insight into the best tactical and strategic practice for the business’ future.

What is Data Science?

Data science is a data-driven industry that builds complex quantitative algorithms to analyse large amounts of information collected through a variety of channels. The results of the analysed data are used to drive strategy and make decisions for an organisation’s future while communicating future market trends, behaviour and the impact of certain events. 

What is the difference between Business Intelligence (BI) and Data Science?

There are many facets to the world of data and how it is used. Originating from the field of Data Mining, Data Science was created as a means to use data to explore future outcomes and using that data to make informed decisions. Data science is known as the ‘forward-looking approach’, while Business Intelligence is the ‘hindsight and insight’ approach, which describes business trends and allows a company to use data from external and internal sources and evaluate the possible impact in the future,  as a result of certain events. A person who works in Data Science is called a Data Scientist and in Business Intelligence, they are called a Business Intelligence Consultant, who are either employed directly or part-time by a company. 

What do BI consultants do?

A company hires the expertise of a BI Consultant to analyse the collected data and determine market and business trends to increase profits and the efficiency of the business. Business Intelligence Consultants use large sections of the data collected, to gain knowledge about current trends and uses this information to assist with making important decisions for the company. To continue our analogy, the Business Intelligence consultant is like the driver of the steam train, together with the directors of the company, advising on which direction to go.

Which Industries use Business Intelligence?

A number of industries use Business Intelligence to benefit their companies in various ways. For example, the oil industry uses Business Intelligence to drive their marketing. As the price of crude oil fluctuates, the data communicates when price is high or low in real-time, which determines when marketing should be pushed or pulled back, saving money and time. The oil industry also uses a combination of geological and seismic data when drilling for oil companies to determine the best method, while keeping costs low. 

The retail industry uses Business Intelligence not only to drive sales, but also reduce and monitor theft. A BI consultant analyses data and determines which product(s) is(are) lost the most due to theft and advises on procedures and policies to be put into place to prevent inventory shrinkage. As a result, the retail company are more inclined to reach its planned profit goals. 

The apparel industry uses Business Intelligence to determine the latest trends. In this highly competitive industry, it is important for a company to be ahead of the game to survive. Business intelligence is used to analyse data and communicate trends.

The use of data and an analyst to communicate relevant data makes a significant change and running of a company. Business Intelligence is not only limited to these industries but can and is used in a variety of industries all around the world. Data Science can also be used to predict changes that need to be made and how those changes will impact future sales or operations. 

What does a data scientist do?

A Data scientist extracts meaning and interprets data using tools and specific methods, from statistics and machine learning. They spend a large amount of time collecting and sorting data, using statistics and software engineering skills. These skills are also used to understand biases or discrepancies in the data. 

Once the data is sorted, the important part is the exploratory data analysis, which consists of both visualization and data understanding. The data scientist observes patterns in the data and uses that knowledge to build models and algorithms, with the goal of understanding product usage and the popularity of the product, using experiments and creating prototypes. The use of data science is an imperative part of decision making in the company. The data is communicated clearly with visuals to the team member, engineers or directors to understand the implications of the way forward in the business.

Which Industries use Data Science?

Data Science is used in a number of industries, such as banking, e-commerce, gaming, finance and insurance, to name but a few. In the banking sector, data scientists are used to monitor financial markets, detect malpractice and audit irregularities. They manage customer data and assist with financial risks, as well as improve the banking experience for customers. 

In the e-commerce industry, data science is used to assist with marketing, services, customising offers and cross-selling. Data scientists analyse customer’s buying patterns, behaviours and history to gain an understanding of the necessary direction for the company to improve their output. 

The gaming industry is synonymous for collecting all types of data on their users and require the services of a data scientist to study consumer behaviour in order to create greater user satisfaction and offer customised products. 

How do you get into the data industry?

Entering into the data industry can be exciting, especially as the possibilities are endless and the industry is continuously evolving. Known as the most popular careers of the 21st century in today’s high-tech world, Business Intelligence and Data Science are an integral part of all types of businesses and organisations who collect data for a wide range of purposes. 

Data scientists and Business Intelligence Consultants come from a variety of educational backgrounds, however, many have studied technical subjects and degrees in computer-related fields. This also includes mathematics and statistics. Studies in human behaviour are also beneficial, as it assists in more accurate conclusions and understanding during consumer data analysis. 

On the job training is also an option, although a keen eye for numbers and data is important, companies use onsite training to help the data analysts to get accustomed with the programs, internal systems and techniques of that specific company, which is not taught in any college or university. 

As it is not a stagnant industry, people in the field need to continually update their skills and partake in training to stay at the cutting edge of information and technology.

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