There’s no doubt that you’ll already know that business intelligence and data analytics are vital to your company, but do you really know what they mean? When looking at business intelligence vs data analytics, the reality is that these are terms that are banded around and they’re often used interchangeably.
In this article, we’re here to clear up the confusion so that you’re in a position to understand the key differences when it comes to analytics vs intelligence. We’re also going to even further and consider data science vs data analytics vs business analytics.
What is business intelligence?
If you’re looking for a definition of business intelligence that’s wordy and full of buzzwords, you can head over to Forrester to find this. There, you’ll find terms that certainly attempt to answer the question ‘What is business intelligence?’, but in our view, it leads to even more confusion. So, we’d like to simplify this. When it comes to defining business intelligence, there are 2 parts that come into play:
1) It’s a term used to describe technologies, strategies and tools that a company uses to obtain business insights. It also refers to how these insights are presented.
2) It is also used to describe the insights themselves – these are the outputs given by the process.
This means that when talking about business intelligence, there needs to be clarity: are you referring to the process or the outcome itself? When looking at the process that’s gone through to obtain business insights, some of the tools and tactics that are utilised include:
- Real-time monitoring
- Dashboard reporting
- The implementation of software such as Power BI
- Data and text mining
- Data Analytics
- Performance management
What this list shows, even though it’s far from exhaustive, is the fact that business intelligence is made up of a variety of processes and tasks. Now, when it comes to business intelligence vs data analytics, you’ll no doubt have noticed the latter in the list above. That’s because it’s a single tool that is part of a wider puzzle that goes into business intelligence.
Business intelligence vs data analytics
The term ‘business intelligence’ was first used in 1865. it appeared in a book written by Richard Mill Devens.
Data analytics has been around since the 19th century. However, the term gained popularity in the 60s with the advent of computers.
Business intelligence is the information required by a company to improve its decision-making.
This is the process where raw data is transformed into a useful format.
The primary goal is to assist with the enhancement of decision making which helps businesses to grow.
The main goals here are data cleansing, data modelling and the transformation of data analytics
There are a variety of business intelligence tools that can be used to implement BI.
There are various data storage systems that can be used. Business intelligence tools can also assist with data analytics.
Hopefully, what the table above demonstrates are the key differences when it comes to analytics vs intelligence. The key takeaway here is that business intelligence exists to support decision-making and it does this by utilising the insights that are provided by data analytics. The latter converts and cleans data so that it can be used in the first place.
Where does data science fit in?
Before data science vs data analytics vs business analytics can be considered, there is a need to understand just what data science is. Often this can be confused with data analytics as there is a degree of cross-over here.
Data science involves building, cleaning and structuring datasets. This is done so that the data can then be analysed and meaning can be extracted from it. While this sounds similar to data analysis, they are separate, and equally valuable, processes. With data science, you’re required to do the following:
- Set hypotheses
- Conduct experiments for data gathering
- Assess the quality of data
- Streamline datasets
- Structure the data so that it can be analysed
What is BI data analysis?
An additional part of the overall picture when considering business intelligence vs data analytics is BI data analysis. If you’re left wondering “What is BI data analysis?” then we’re here to help.
A BI data analyst has a role that includes utilising BI tools. By using these tools, the analyst identifies business-focused insights that have an influence on business decisions as a whole. The role of BI data analysis is to use an evidence-based approach to provide intelligence to a company.
An analyst will create dashboards and reports that are able to highlight key insights that a business needs to understand. Of course, before this can be carried out, the analyst requires an in-depth understanding of the business that they are operating in.
Business intelligence and data analytics: choosing what’s right for you
So, when considering business intelligence vs data analytics, you may be lacking clarity when it comes to deciding what your business needs. One key point here is that business intelligence needs data analytics. The reality is that the former can’t function without the latter. However, while data analytics are used in business, they can function perfectly well without business data.
What business intelligence has become is the dominant way that data analytics is used. The latter, however, is used in an array of other fields too.
Frequently asked questions
1) Data analyst vs business intelligence analyst, is there a difference?
The role of a data analyst is to identify the patterns that exist in data and then go on and produce actionable insights. A business intelligence analyst has a greater focus on the operation side of things.
2) What skills are required for business intelligence?
A business intelligence analyst is likely to have a data analysis focused bachelor’s degree or master’s degree. They need knowledge of a wide range of BI platforms as well as the ability to manage budgets. Communication skills are a must.
3) What skills are required for data analytics?
The ability to work well with probability and statistics and well as being able to demonstrate problem-solving and critical thinking. Knowledge of Python, SQL and MS Excel is also needed.
4) Does business intelligence include data analytics?
Yes, as we have seen business intelligence can not exist without data analytics.