Both Business Intelligence and Data Science enable data analysis and decision support. However, these two disciplines have important differences. This article explores the link in BI and computer science and how to train your employees to take full advantage of it.
Previously, Business Intelligence was primarily descriptive. Business intelligence was primarily used to deliver static reports on business results.
But in the face of the explosion in the amount of data, the increasing complexity of information and the emergence of new technologies, Data Science has quickly become crucial. In fact, these two disciplines are closely linked despite their differences.
What is Data Science and Business Intelligence?
To fully understand the relationship between BI and Data Science, it is important to clearly define these two terms in advance. First and foremost, computer science consists of using a wide range of tools and techniques to extract meaning and information from the vast amounts of data that the company has available.
Business Intelligence, on the other hand, allows you to monitor the current state of your company’s data to understand the history of its performance. In summary, BI consists of interpreting the collected data, while Data Science makes it possible to analyze this data to make predictions about the future. Business Intelligence is mainly used for reporting or descriptive analysis, while Data Science is used for predictive or prescriptive analysis.
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What are the similarities between the two?
From these descriptions, one can identify clear similarities between BI and Data Science. Both disciplines focus on data, with the goal of bringing benefits to the business. This may be to increase revenue, better retain customers or conquer new markets.
In both cases, the goal is to interpret the data. This interpretation requires the expertise of a specialist who is able to extract useful information from the results of the analyzes.
Both computer science and business intelligence offer decision support to business leaders, executives and executives. We are talking about “data-driven” decisions.
The main differences
In addition to these commonalities, Data Science has important differences with Business Intelligence. It enables high-speed processing of huge amounts of data, with complex and diverse structure from a wide variety of sources. On the contrary, BI only allows support for static, formatted and structured data.
Computer science was born out of the need to not only create reports from past data, but to predict future trends and give advice based on them. Thanks to self-service tools and automation via Machine Learning, Data Science is also accessible to everyone, whereas Business Intelligence was reserved for IT experts.
We can conclude that Data Science democratizes data analysis. According to Research and Markets, the self-service market for business intelligence will reach $ 7.3 billion by 2021 and will give “citizen data researchers” access to the benefits of analytics without technical expertise.
In addition, Business Intelligence platforms are not suitable for Big Data analysis. Data has become too complex and large for traditional tools.
For many experts, Data Science is ultimately a development of Business Intelligence. These two disciplines aim to support decision making, but their approaches are radically different.
Finally, it is important to note that Business Intelligence focuses only on data analysis. Data Science, on the other hand, also includes data management and data visualization.
How does Data Science strengthen Business Intelligence?
Despite these differences, Data Science and Business Intelligence are complementary. If Business Intelligence has always made it possible to support the decisions of managers and executives, computer science has enabled them to become autonomous in data analysis.
Ideally, a Business Intelligence team can take care of operational analytics, while a team of Data Scientists improve BI and analytics tools to automate them. In this way, all employees can achieve productivity and independence.
BI analysts can even prepare the data so that data scientists can use it to feed their algorithmic models. Business Intelligence experts can offer their understanding of business analytics needs to help data researchers build powerful prediction models.
In short, BI experts and Data Scientists have their place in an analytical team. The former provides reports, while the latter develops solutions for the future. Together, they can build a powerful internal analytics platform for business users.
How do you train your employees in Data Science and BI?
Both Business Intelligence and Data Science offer valuable benefits to your business. To take advantage of this, however, it is necessary to master the tools and processes of these disciplines.
To acquire this expertise internally, you can train your employees and partners. There is a wide range of options: MooC, BootCamps, continuing education, etc.
In addition, more and more companies are seeking certifications issued by publishers of Business Intelligence tools, such as Microsoft’s Power BI tool. These certifications are obtained by passing an exam. To set the odds on your side, it is recommended to undergo a workout dedicated to Power BI.
It is important to choose training designed by experts and corresponding to the real needs of the company. It should also offer flexibility that is compatible with professional activity and ideally could be funded through the personal training account.
By choosing the right training, you can allow your teams to develop new skills while continuing their activity. Subsequently, you will be able to use the data you have at your disposal for better decision making.