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The Role of Data Science in Business Intelligence


Nowadays, it’s rather difficult to discuss business without hearing or mentioning terms like Data Science and Business Intelligence (BI). However, if you press someone talking about these terms for details, you’ll soon find out that most use them as buzzwords since not many people really understand the meaning behind the words.

Therefore, in today’s article we will discuss the two terms separately, and then take a look at why both have an important role in the world of modern business.

Data Science in Business

At its core, data science is a multi-disciplinary field that combines the powers of Mathematics, Statistics, Programming, and several other disciplines to create a new one. Experts in data science are tasked with:

  • finding patterns within the data collection they study
  • analyzing and interpreting the patterns they find
  • maintaining the data
  • generating predictions
  • manipulating and extracting various information

Moreover, data science specialists need knowledge in the field of Machine Learning (ML), Artificial Intelligence (AI), and other advanced fields in order to be able to make accurate predictions and extract insight from the data.

So, what does this highly technical field has to do with business?

As you probably can tell, the key phrase here is data analysis and predictions based on real-time data collections. Businesses everywhere have the amazing chance of getting a real insight into the lives and way of thinking of their target audience. However, you can’t do so without proper data collection and storage methods and the right people or tools to interpret the data and process it into usable reports.

How for data science to work and produce results, most businesses need the help and guidance of an expert consultant (company or individual) that can help with training and guidance during the implementation and after.

In summary, Data Science is all about collecting, manipulating, and processing data.

Business Intelligence

Business Intelligence is considered to be part of the bigger picture that Data Science can paint and it’s a platform designed to help businesses make sense of their environment (hence, Business Intelligence).

With BI-powered tools, executives and managers can have a better understanding of what Data Science is trying to communicate. Therefore, BI is all about collecting, analyzing, and presenting the data in a format that’s easy to understand and allows non-specialists to draw conclusions. This happens because BI platforms produce reports, summaries, graphs, charts, and dashboards using the predictions and visualizations produced by Data Science.

In summary, organizations that use BI are able to make better-informed decisions and act according to the changes in the market. Therefore, BI is a must-have tool for strategic, data-driven decisions.

Data Science vs Business Intelligence

As you can tell by now, both terms are data and information-centric and both disciplines make use of statistical methods to produce usable insight. However, there is a clear difference between the two, with BI being supported by Data Science.

The beginnings of BI are founded in the records each business used to keep on their local data center (usually a few servers, cut from the internet). These records used to contain structured transactional information specific to said business and a few external sources. Therefore, BI started as a method to process already existing data, stored neatly in relational tables, in order to produce dashboards and key metrics to help decision-makers understand what happened and why.

On the other hand, Data Science is focused on the future (predictive analysis) and tries to understand what will happen based on the datasets it has. Therefore, this field is more about making predictions and understanding how various factors may affect the outcome.

However, nowadays, BI tools also use predictive analysis to create a broader view for decision-makers. Still, in order to make full use of Data Science, businesses need to implement highly automated processes and systems to allow the algorithms to work as the data is collected. In short, Data Science allows Business Intelligence to change perspective and take a look into the future.

Wrap Up

From a business’s perspective, Data Science and Business Intelligence have a common goal – to deliver valuable and actionable data that can be easily interpreted by decision-makers. Both are extremely useful tools and have helped bring businesses into the modern world.

In summary, due to these two advanced tools, businesses can now run highly efficient PPC marketing campaigns while also putting together strategies to increase the number of visitors and potential leads on the site.

Lastly, businesses and organizations that are still afraid to take the step towards automation and data-driven decisions are bound to be left behind by the competition. Those that do, must take all necessary precautions to ensure data integrity is always at its best levels.

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