You may be thinking that Data Analytics and Business Intelligence are the same. However, that’s not the reality. You will find both the terms used interchangeably. But, there are slight variations in each of its definitions.
What is Data Analytics?
Data analytics means the science of studying raw data by making data sets to draw conclusions. These conclusions are a result of the information present in those data sets.
Mostly, data analysis is done with some specific software tools. Data analytics technologies are used on a large scale. For instance, you will find them in commercial industries to make more informed business decisions. Scientists and researchers also use data analytics. They approve or disapprove any scientific hypotheses, models, or theories.
In a literal sense, the term data analytics is an assortment of applications. It ranges from basic reporting and online analytical processing (OALP). Further, it also includes business intelligence (BI), and different types of advanced analytics. That way, it is like business analytics, another broader category of techniques to analyze data.
The basic variation lies in the fact that “data analytics” focuses on wider subjects. On the other hand, “business intelligence” is inclined towards business uses.
With the help of data analytics, the companies can improve operational efficiencies. They can also increase revenues, better customer service efforts, and optimize marketing campaigns. Businesses can also use it to respond with precision to upcoming market trends. As a result, it helps them to gain an edge over competitors. In the end, data analytics’ end goal is to enhance business performances.
Subscribers to r/BusinessIntelligence (“a subreddit dedicated to creating data-driven decisions via dashboards, reports, alerts, and ad-hoc analysis”) experienced massive growth in the past 5 years from ~6k subs in 2017 to ~85k subs in 2021. That’s a 1316.67% increase!! And it speaks a lot about the department.
Examples of Data Analytics
When it comes to real-time data analytics, the data is analyzed as soon as it is available. This enables businesses to have deep information and draw conclusions as quickly as the data is entered. In this way, it assists businesses react quickly and provide better services and products. The business will be able to go ahead of the curve by using real-time data analytics.
Some of the major real-time data analytics examples are:
- Information security
- Real-time credit scoring
- Customer relationship management
- Fraud detection
We come across so many real-life data analytics examples in our day-to-day life. Let’s see a simple and quick example.
You most likely know this if you love food. It is applicable for restaurants as well as food delivery services. Now, when you are a regular user of any food delivery or restaurant app, you receive an email. In that it states, “We miss you!” or “We wonder where you are?” You get such emails when you haven’t used their services for a while.
In fact, these emails try to lure customers with special offers and discounts. These food delivery services and restaurants use guest management software. It monitors the ordering habits of the guests and customers. These software tools offer email campaigning for the targeted customers. Thus, it helps improve business performance.
Another very common example is e-commerce. Suppose you visit any online shopping site and start your search for any specific product. You will receive several recommendations of the product from many other brands within seconds. Here, data analytics should do its work very carefully. If you are searching for earphones, it is giving you recommendations related to earphones. – Please check: https://towardsdatascience.com/data-analytics-in-e-commerce-retail-7ea42b561c2f
Now that’s how Data Analytics work.
What is Business Intelligence?
Business Intelligence (BI) uses software and services to convert data into actionable knowledge. These can be useful for workers, managers, or executives. And, this knowledge becomes the basis of an organization’s tactical and strategic business decisions.
BI tools analyze and access data sets. Organizations collect data through internal IT systems and outer sources. Next, they prepare this data for analysis and run queries against given data. Then, they create visuals, BI dashboards, and reports. Later, organizations use the results for planning and operation decision-making.
The analytical findings are present in various forms. It offers users in-depth intelligence regarding the condition of the business. For instance, you can see them as graphs, maps, charts, summaries, reports and dashboards.
The term business intelligence often means a variety of tools that offer quick and easy-to-use information. This is in terms of the current state of an organization/business based on the given data.
Business Intelligence architecture doesn’t only contain BI software. BI data is stored in a data warehouse, specially built for a company. Just as you have a product in a particular department of a shopping mall.
Examples of Business Intelligence
Reporting is the focal point of business intelligence. Most probably, the dashboard refers to as the core business intelligence tool. Dashboards are hosted software apps that automatically put all the available data in graphs and charts. These provide information about the company’s current condition.
Business intelligence doesn’t offer any information to business users about what they ought to do in a certain situation. Also, they don’t tell you what will happen if they take or don’t take a specific action.
Specifically, it isn’t all about generating reports. Instead, BI provides a means for people to study the given data to learn the recent trends and derive insights. It does that by understanding the efforts needed to find out, mix and query the data required to make appropriate business decisions.
Let’s take an example of a company that wishes to manage its supply chain properly. If the product to be delivered gets delayed in some way, the company should be able to know the process level that must have caused the delay. In addition, it needs to know all the places where variabilities are present within the shipping system. For example, the company should find out whether there are any set of products that cause delays or the mode of transportation is not working efficiently for the delivery. This company can also use its BI abilities to explore which products face the issue of delay most frequently. You can understand which transportation usually causes delays.
The potential scope of business intelligence sees far more than what the world perceives of it. It is not just used to reduce costs and improve sales. A co-op organization can use it to maintain the record of retention and member acquisition. BI tools are capable of generating sales and delivery reports automatically by using CRM data.
In a nutshell, both data analytics and business intelligence rely heavily on data. Since there is a lot of information to use, making its correct use is important. And, that’s where you will rub yourself across these terms.