Acquiring valuable information from data is the number one priority of any organization. To do this, companies use various Business Intelligence tools to extract data from multiple data sources, visualize them, generate reports and dashboards that can be used by multiple users to better understand their client’s requirements. This whole process is called Business Intelligence Analytics.
Business Intelligence Analytics plays an important role in helping organizations become data-driven. It incorporates all the software, hardware and expertise of multiple teams to make strategic decisions.
In this article, you will learn about the importance of Business Intelligence Analytics for any organization. You will also learn how data can be a valuable asset in this process with some real-world examples. Furthermore, you will also be introduced to Business Insights in this process and how you can choose the correct BI tool depending on your business needs. Read along to find out how Business Intelligence Analytics plays a major role in developing your organization.
What is Business Intelligence
BI is an umbrella term that encompasses the collection, pruning, analysis, and presentation of business data; to use it to make correct and optimal business decisions and to increase performance. BI includes all the software, hardware, best practices, and expertise that goes into this process.
It unveils the real picture and provides insights into a business’s various operations, facilitates correct business decisions based on actual data and not on intuition or gut feelings.
BI can also forecast future trends, changing market dynamics, variations in demand and supply, and predict lean and thick periods. Nevertheless, the final results of BI should be simple enough to be understood by non-technical users. Users must be able to sift through the provided knowledge, delve deeper by using filters and drill-downs, and create new “what-if” or “alternative” scenarios.
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Introduction to Business Intelligence Analytics
Data plays a vital role in Business Intelligence Analytics. Data by itself is just a set of numbers, with 1 or more numerical values, a standalone datum does not carry much meaning, but when it’s combined with related data, compared with its peers, processed with other data to derive metrics, seen in its appropriate context; then a datum can provide you with valuable insights.
You can also take a look at what is a BI Dashboard along with examples to get a better understanding of Business Intelligence Analytics.
The above concepts can be explained by a very simple example.
Let’s assume that there is a real estate sale and leasing company operating in a particular geography. It needs to know which areas to focus upon, where to place most of its agents, or open new offices. Let’s say they have this simple data (shown below) to start with:
Image Source: Self
Using the above data, and applying some Business Intelligence Analytics to it, we can draw a heatmap that depicts the location of the properties in question. This heatmap is also based on their price and relevance to the performed searches and is shown below.
Image Source: Self
The above heatmap clearly shows the areas of the target city where most of the relevant properties are concentrated. It also depicts the areas where business opportunities are few and far in between, i.e. the fringe areas with greenish and bluish hues.
This simple analysis and related graph/heat chart show where the sale/leasing efforts should be focused and the best geographies where agents could be placed or new offices opened.
It’s much simpler and much more intuitive than just skimming through the raw addresses data, trying to find areas where most properties exist. Also, it allows you to use filters and selection criteria, to further investigate and create new “what if” scenarios.
Introduction to Business Insights
An insight is a deeper and more meaningful look at something. Business Insight is the idea of having a deeper understanding of a business process, a careful and penetrative analysis of a situation, an exercise to gain more intelligence, given a set of facts.
It plays a vital role in Business Intelligence Analytics and is aimed at enhancing competitiveness, increasing profits, and improving the sustainability of an organization.
Uses of Business Intelligence Analytics
Business Intelligence Analytics helps organizations find significant information easily and identify business trends to keep up pace with their changing customer demands.
Broadly speaking, there can be 5 stages of Business Intelligence Analytics – Data collection –> Data analysis –> Situational awareness –> Risk assessment –> Profitable execution.
Business Intelligence Analytics Examples
The real-world Business Intelligence examples are listed below:
- Increasing Sales: Business Intelligence Analytics is used to set right the inconsistent sales. The retailer can look at the sales pattern and plan on methods to increase sales.
- Strategize marketing plans: With the demographic information of the current customers and target customers, the retailer can study the buying pattern and identify the strong sales point. You can segment buyers and customize a marketing strategy for each group.
- Improving financial efficiency: Business Intelligence Analytics can be used to study the growth of your company, the reason for low collection percentage, the reason for excessive claim denials and high balance of money, and many other insights to improve financial efficiency.
Business Intelligence vs. Business Analytics
Here is a comparison table between Business Analytics and Business Intelligence:
| Basis for comparison | Business Intelligence | Business Analytics |
| Definition | Analyses past and present data to meet your business needs | Analyses past data to meet your current business needs |
| Usage | To run business operations | To change business operations and improve productivity |
| Ease of Operations | For current business operations | For future business operations |
| Tools | SAP Business Objects, QlikSense, TIBCO, PowerBI, etc., | Word processing, Google docs, MS Visio, MS Office Tools, etc., |
| Applications | Apply to all large-scale companies to run current business operations | Applies to companies where future growth and productivity as its goal |
| Field | Comes under Business Analytics | Contains Data warehouse, information management, etc., |
Table Source: EducaDetermine your Business Intelligence and Analytics needs
It is not between Business Intelligence or Business Analytics, both descriptive and predictive analytics are essential for a Business Intelligence analyst to pull insights. The major area to focus on is what you need the data system to do and who will use the tool more than the BI vs analytics. Developing a business intelligence strategy is an important first step in implementing a BI solution. Ask important questions, such as:
- Who are the key stakeholders?
- Who will be using this system?
- What departments need business intelligence and what will be measured?
- What support do content authors and information consumers need?
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How to Choose the Correct BI Tool?
BI tools should allow for auto-refreshing of charts and updating of reports, as soon as the underlying data undergoes some change. This keeps the management and stakeholders abreast with the latest information.
Our second example is a bit more evolved.
Let’s assume that an Ice Cream company sees a surge in their demand in the summer months, and the business done in that period is the main source of their yearly sales and profit. The given scenario is depicted in the graph shown below.
Image Source: Self
But this very warmer/hot season presents challenges in transporting their product(s) quickly to consumption centers, whilst keeping them in pristine ( frozen and fresh) condition.
A proper BI analysis can help in faster production and in identifying bottlenecks in freight movements. It can pinpoint the modes of transport that are most suited given the high demand, high perishability, and low consumption threshold.
This BI Analysis is shown in the graph given below.
Image Source
The insights given by BI can help formulate a quicker and efficient production, transport, and warehousing strategy. Moreover, the high demand season is already known, the company can prepare to be nimble and agile, during the demanding months.
What are the Benefits of BI & Analytics?
- Informed Decision-Making: BI and analytics provide data-driven insights to make smarter business decisions.
- Improved Efficiency: Streamline processes and reduce operational costs by identifying inefficiencies.
- Competitive Advantage: Stay ahead of competitors by understanding market trends and customer behavior.
- Risk Reduction: Identify potential risks early through data analysis, helping mitigate losses.
- Enhanced Customer Experience: Tailor products and services to customer needs by analyzing behavior and preferences.
Future Uses of BI Analytics
Business intelligence Analytics evolves according to business needs and technological advancement. You need to identify current trends to be updated with the new innovations. The growth of Artificial Intelligence and Machine Learning will be enormous and businesses can always integrate the insights from AI into a broader BI strategy. Data visualization will be even more essential to work together across teams and departments. BI Analytics has scope in real-time sales tracking, allows users to discover insights into customer behavior, forecast profits, and more. It can impact a lot of industries like retail, insurance, and oil have.
Conclusion
This article provided a comprehensive guide on Business Intelligence Analytics and explained its importance to any organization. It also provided a brief introduction to Business Insights and explained the uses of Business Intelligence Analytics. Furthermore, it also explained how to choose the correct BI tool. Overall, Business Intelligence Analytics plays a pivotal role to improve the decision-making processes and also enhances tactical and strategic management. It also helps organizations find significant information easily and identify business trends to keep up pace with their changing customer demands.
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Frequently Asked Questions
1. What does an intelligence analyst do?
An intelligence analyst collects, analyzes, and interprets data to help organizations make informed decisions and predict future trends or threats.
2. What is the meaning of intelligence analysis?
Intelligence analysis involves examining data to uncover patterns, trends, and insights that can guide decision-making and strategy.
3. What is an example of intelligence analysis?
An example of intelligence analysis is analyzing social media data to identify potential security threats or tracking financial transactions to detect fraud.
Pratik Dwivedi is a seasoned expert in data analytics, machine learning, AI, big data, and business intelligence. With over 18 years of experience in system analysis, design, and implementation, including 8 years in a Techno-Managerial role, he has successfully managed international clients and led teams on various projects. Pratik is passionate about creating engaging content that educates and inspires, leveraging his extensive technical and managerial expertise.
