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Business Intelligence and Data Science – a managerial perspective

date: 15 September 2022
reading time: 5 min

Data, data everywhere! Understanding its value and unlocking its potential can lead to business growth on an unprecedented scale. With help from business intelligence (BI) and data science (DS), managers are now able to ensure that their organisations stay ahead of the competition. How? By predicting future trends, detecting and preventing serious threats, discovering well-hidden opportunities, opening up new streams of revenue, and drawing relevant conclusions from past mistakes, etc.

Today, I’m going to briefly outline the idea behind incorporating Business Intelligence (BI) and Data Science (DS) into your business strategies, in order to give you a taste of the benefits. So, let’s go from general to specific and start with defining the terms.

Of course, there are no universally accepted definitions, but I will try to capture the essence…


What is Business Intelligence?

Business intelligence supports decision-making based on current and historical data that are turned into actionable insights with the help of advanced yet relatively easy-to-use tools. This helps managers understand the current state of a company by analysing and visualising business information.


What is Data Science?

Data science, on the other hand, involves many disciplines in order to create forecasts. It uses statistics, machine learning, programming, and descriptive and predictive analytics, etc. — usually aimed at solving very complex problems. DS enables high levels of personalisation and makes it possible to accurately predict future trends, expectations, and market requirements.

Does this sound a bit too general? Well, even though both business intelligence and data science deal with data — they differ greatly in the details.


What are the key differences between Business Intelligence and Data Science?


Business intelligence

First and foremost, BI discovers past and current trends, so that an organisation can adjust their present strategy accordingly. This is used to support decision-making on a daily basis and for creating reports that can be presented to potential investors or stakeholders.

More importantly, BI doesn’t require very technical skills — just basic knowledge related to statistics and business, as well as some analytical skills. And, of course, it is also important to master some business intelligence tools, like Microsoft Power BI or Oracle BI, as they can finish the job for you with, for example, data visualisation. Because being able to present data in an interesting, clear and easy-to-digest way is not only helpful in decision-making, but also for attracting the attention of business VIPs. Also, BI deals with structured and well-organised data, which is easy to filter, sort, process, and analyse.

All of this means that it is not that difficult to learn and understand business intelligence, even without any technical background. As a result, involving BI in your daily business operations is definitely less costly than data science.


Data science

DS takes a forward-thinking approach and is used to prepare forecasts for the future. It’s aimed at exploring and discovering patterns in a sea of information, and also for handling very complex, multilevel problems.

However, serious issues require serious measures. That’s why data scientists need to possess more technical skill sets that combine coding, machine learning, data mining, and advanced statistics, etc. Having a remarkably logical and analytical mind is a must here, along with deep domain knowledge.

DS also manages large volumes of dynamic and unstructured (or less structured) data, which can oftentimes be hard to explore, especially when you’re trying to find some commonalities.

No wonder data science is more expensive than business intelligence. Instead of reports and dashboards (which are characteristic of BI), we use hypothesis testing and also build statistical and predictive models — invaluable in terms of planning on a strategic level.


How can Business Intelligence and Data Science help businesses?

As you might have already noticed, the question is not whether to bet on BI or DS, but rather how to combine them wisely to make the most of your data, because each case is different. It is likely that you will need to hire either a dedicated data expert or an IT partner who can handle this for you.

From a managerial point of view, this is really worth the effort and investment, for at least a few different reasons:

  • Detailed insights

    You will get highly accurate and detailed insights which can help you understand your target audience better and gain an in-depth view of your organisation — its processes, financial performance, and business problems, etc. This is absolutely crucial if you want to make better and faster decisions.

  • Optimisation of processes

    By detecting operational inefficiencies, you can easily become more organised and get rid of any bottlenecks that are just slowing you down. Plus, you can improve the processes related to customer service — in order to better satisfy your repeat clients and also attract new ones.

  • Enhanced security

    Cybersecurity data science is a relatively new concept which includes a bunch of advanced and innovative methods used to identify and reduce or prevent possible threats. Hostile cyberattacks are becoming increasingly cunning, so preventative measures have to be more sophisticated now than ever before.

  • Better products

    When you spot any signs of an emerging market trend early on, you can react immediately and upgrade your existing app with corresponding features, or even create a brand-new product. Answering your clients’ future needs and providing a superior user experience may be key to staying ahead of the competition.

  • Trend setting

    You may also want to actively shape the future of your industry by creating new trends. Data science will help you test and foster innovative ideas, and not only respond to your audience’s requirements.


Wrap-up

In conclusion, data science and business intelligence are great decision-making tools, enabling fast reactions, both in terms of strategic planning and daily activities. Combined, they provide high levels of automation in management processes, empowering leaders and executives to handle their data in the best possible way. And the technology is constantly and rapidly evolving, incorporating more and more machine learning, and increasing the accuracy of hypothesis testing. This, in turn, allows companies to develop even better solutions.

So, if you’re still on the fence about it — don’t hesitate to get in touch with us. We’ll be happy to help and answer any questions that you may have.

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