Business Intelligence vs Business Analytics. In today’s business world, access to information and analytical skills have become critical to the success of an organization.
Having the ability to understand data and make decisions based on accurate and reliable information is essential. It is in this context where two approaches emerge that contribute to improving business intelligence and analysis: business intelligence and business analytics.
¿What is business intelligence?
Business intelligence consists of the set of technologies, tools and processes used to collect, analyze and present relevant business information.
Its main objective is to provide decision makers with a complete and accurate view of data, in order to improve decision making and increase the operational efficiency of an organization.
Business intelligence is based on data extraction, transformation and loading (ETL), data storage, data processing and analysis, and data visualization and presentation.
Benefits of business intelligence
Business intelligence provides a series of benefits to companies that use it effectively. These benefits include:
- Improved decision making: Business intelligence provides accurate and reliable information that helps decision makers evaluate different scenarios and choose the best option.
- Identification of growth opportunities: Business data analysis can reveal new market opportunities, customer segments, and potential products or services.
- Business Process Optimization: By analyzing data, organizations can identify inefficiencies and areas for improvement in their processes, allowing them to optimize their operations.
- Detection of trends and patterns: Business intelligence allows the analysis of large volumes of data over time, allowing the identification of trends and patterns that can be used to make strategic decisions.
- Increased operational efficiency: By providing a complete view of data and processes, business intelligence helps organizations optimize their operations and reduce costs.
¿What is business analytics?
Business analytics is an approach that focuses on analyzing data to obtain useful and predictive insights. Unlike business intelligence, which focuses on the presentation of historical data, business analytics seeks to leverage data to predict the future and make decisions based on that information.
The business analytics process generally includes data collection and cleaning, exploratory data analysis, modeling and construction of algorithms, and interpretation and visualization of results.
Types of analysis in business analytics
Business analytics uses different types of analysis depending on the objective and situation. The main types of analysis used in business analytics are:
- Descriptive analysis: This type of analysis focuses on describing the data and understanding what has happened in the past.
- Predictive analysis: Through statistical and data mining techniques, predictive analysis seeks to predict future events and trends.
- Prescriptive analysis: This type of analysis uses models and algorithms to recommend actions or decisions based on available data.
Business intelligence vs Business analytics
Similarities between business intelligence and business analytics
Although business intelligence and business analytics have different approaches, there are similarities between the two that are important to highlight. Both approaches aim to extract useful insights from business data and contribute to informed decision making.
Differences between business intelligence and business analytics
Despite the similarities, there are also significant differences between business intelligence and business analytics:
- Approach: While business intelligence focuses on the presentation of historical data and the analysis of past trends, business analytics seeks to predict the future and make decisions based on those predictions.
- Tools and technologies used: Business intelligence is based on tools and technologies that allow the visualization and presentation of data, while business analytics uses more advanced techniques, such as machine learning and statistical analysis.
- Level of detail: Business intelligence provides an overview of the data, while business analytics focuses on detailed and in-depth analysis of the data, with the aim of discovering hidden patterns and trends.
Business intelligence and business analytics applications and use cases
Both business intelligence and business analytics have applications and use cases in various industries and sectors. Some examples of practical applications of both approaches are:
- In the marketing sector, business intelligence and business analytics can be used to analyze customer behavior, identify profitable market segments, and develop personalized marketing strategies.
- In the financial sector, both business intelligence and business analytics can be used to analyze transaction data, evaluate credit risks and predict market movements.
- In logistics and supply chain, business intelligence and business analytics can be used to optimize delivery routes, manage inventories and predict future demands.
¿Which is better: business intelligence or business analytics?
There is no one approach better than the other
One approach cannot be established as better than the other, since both are complementary and are used at different times and business contexts. Business intelligence provides a general and accessible view of the data, while business analytics allows for deeper analysis aimed at predicting future events.
Importance of combining business intelligence and business analytics
However, it is important to highlight that the combination of both approaches can generate greater value for companies.
By combining business intelligence and business analytics, organizations can gain a complete and deep view of their data, allowing them to make more informed and strategic decisions.
For example, business intelligence can provide an overview of data that helps identify patterns and trends quickly and efficiently. Business analytics can then be used to further analyze these patterns and trends and predict future events.