Distinguishing Information Analytics As Well As Business Intelligence Tools – If someone puts you on the spot, can you tell them what the difference is between business intelligence and analytics? If you’re a little unsure about the specifics here, you’re not alone, experts disagree too! There is no clear line between business intelligence and analytics, but they are extremely connected and intertwined in their approach to solving business problems, providing insights on past and present data, and defining decisions future While some experts try to underline that BA focuses, too, on the predictive model and advanced statistics to assess what will happen in the future, BI is more focused on the present moment of the data, making the decision based on the current insights. But let’s see in more detail what the experts say and how we can connect and differentiate the two.
We have already seen earlier this year the benefits of Business Intelligence and Business Analytics. Let’s dig deeper now and understand what this is all about, what makes them different, and how they complement each other.
Distinguishing Information Analytics As Well As Business Intelligence Tools
In an article covering BI and Business Analytics, Better Buys asked seven different BI professionals what they thought about the difference between business intelligence and analytics. Every professional has a different one. Here are some snippets of his views:
Holistic Data Guide
“BI looks in the rearview mirror and using historical data. BA looks ahead of you to see what’s going on.”
“What is the difference between Business Analytics and Business Intelligence? The correct answer is: everyone has an opinion, but no one knows it, and you shouldn’t care.”
Well, what do you care about the difference between business intelligence and data analysis? It doesn’t matter if you run an operation or a small business, if you have to make decisions that affect you in the short or long term, it’s wise to use both. BI and BA will provide an organization with a holistic view of raw data and make more successful and efficient decisions.
Business intelligence and analytics are data management solutions implemented in companies and enterprises to collect historical and current data, while using statistics and software to analyze the information first, and provide insights to make better future decisions.
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Let’s face it: both terms provide insights into business operations and future decisions, but it’s about the differences in how they do it and what information they precisely provide.
It seems clear that there is no standard “correct” definition of the differences between the two terms. The varied opinions given by the experts are proof of this. Therefore, instead of trying to find the “right” answer, let’s find a useful distinction between the two that can be used simply and clearly to help you in your work. The most direct and useful difference between business intelligence and data analysis boils down to two factors:
Keeping in mind that this is all a matter of opinion, here are our simplified definitions of business intelligence versus business analytics.
It happened that leads to the present moment. It identifies big trends and patterns without digging too deep
Business Intelligence In Decision Support Systems
That said, BI and BA have different applications. On the one hand, BI tools can help organizations identify relevant trends as well as the explanation of various past scenarios. On the other hand, BA is concerned with more advanced applications such as predictive analysis and statistical modeling. This also allows the two complementary terms to provide a complete picture of the data. By using Business Intelligence and Analytics (ABI) tools, companies can extract the full potential from their analytics efforts and make better, fact-based decisions.
Still confused? We will use an example from football as a metaphor to help clarify everything we have said.
Let’s say you’re on the coaching staff of a football team and you want to review the most recent game. Do this to see how you can fix your mistakes and replicate your successes.
Using our previous definitions, BI would be the process of identifying all the stats and plays that led to your winning team. It could identify that you have held possession of the ball for much longer than your opponents. You could also identify the tendency that your right side of the field was instrumental in maintaining possession through excellent passing.
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You had possession of the ball more than your opponent and because your right side of the field did so well to pass.
These questions are important. They allow you to understand how you can replicate your success, or prevent your failure later. Asking the right business intelligence questions will lead to better analysis. While using a business dashboard, all your information can be streamlined in a single place, making the time for meaningful decisions much faster. But first, we need to analyze the difference more, because that will help us understand what to do in the operation process of a company, and how to choose the best tool to manage your insights.
As the introduction of this post, there is no clear distinction between BI and BA. While the two terms can often be used interchangeably, there are a few things that differentiate them. Let’s look at each of them separately.
The first difference between the two concepts is in the actual definition. While both serve a purpose in the analytical process, they do not serve the same purpose. A fundamental differentiating factor is in the method that each uses as a basis. While BI tells you what happened in the past and what is happening now (descriptive analytics), BA tells you what will happen in the future (predictive analytics). Let’s see a conceptual definition of both.
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Usage is another factor that can help you understand how BI and BA differ from each other. In this case, not only the end user changes, but also the purpose of use. As we have mentioned again and again, BI tools are used with the aim of reporting on the current and past performance of the organization, BA tools allow you to go a step further, helping to decide of your next steps. Let’s see with an example.
Imagine you own a shoe online. One day you look at your sales report and notice that sales for a pair of red shoes have increased in recent weeks in New York. This information is provided by your BI tool and allows you to understand that you need to produce more red shoes to cover the demand. Now, BA can help you understand why sales have increased specifically in New York. Going further into your website, you see that most of the traffic is coming from a NY blogger who wore your red shoes. Like this, he decides to send some other models of successful shoes to other bloggers in the country and prepare the production based on the historical demand.
The end user is another factor to consider. Most of the BI software in the market are self-service. Meaning, anyone without the need for technical skills can use it, making the BI analysis process more intuitive and easy to do. On the other side of things, BA is more technical. It relies on mathematical models, machine learning and artificial intelligence technologies to make accurate predictions which makes them more difficult to use for an average user without prior skills. However, this has changed in recent years as new tools have emerged that allow users to perform advanced analysis with a few clicks.
Our third and final differentiating factor is in the application. Your data is used differently depending on whether you are analyzing BI or BA. While BI organizes information into easy-to-understand reports, BA brings a little more to the information. Let’s look at the applications of each of them.
What Is Data Mining? How It Works, Benefits, Techniques, And Examples
In the next part of this post, we will examine BI and BA from a business perspective with use cases and examples, but first, we need to examine the distinction between correlation and causation.
When two things are correlated, it means that when one happens, the other tends to happen at the same time. When two things have a causal relationship, it means that one thing directly or indirectly leads to the other happening.
A famous example of the difference between these two is the fact that ice cream consumption and homicide rates in cities are highly correlated. Now, of course, ice doesn’t make people kill themselves. So clearly there is no causal relationship.
The two are correlated due to the fact that homicide rates increase when temperatures rise in late summer. It is theorized that since warmer weather brings more people outside, this leads to more social interactions, some of which are violent.
What Is Data Mining? Finding Patterns And Trends In Data
You can find examples of people confusing correlation and causation anywhere you look. For example, that muscular person at the gym who always likes to give you workout advice may or may not really know what they’re talking about. The advice they give you, while they are related to being known by a muscular person,
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