how do business intelligence and business analytics support decision making
Both business intelligence (BI) and business analytics (BA) play a crucial role in guiding business decisions across various processes such as marketing, research and development, and inventory management. They aim to assist companies in making smarter decisions through the analysis of business data. BI and BA are rapidly evolving due to the increasing availability of data and improved tools. While it may initially seem that BI and BA are the same, they differ in their methods and objectives.
Business intelligence utilizes past and present data to draw conclusions, while business analytics uses a range of data along with sophisticated and complex tools to attempt predictions. It is important for businesses to understand the often subtle differences between the two and how each can add value.
BI and BA promise to provide accurate and near-real-time information to decision-makers, and analytical tools assist them in quickly understanding information and taking action. The BI environment consists of data from the business environment, BI infrastructure, BA toolset, users and managerial methods, BI delivery platforms (management information systems), decision support systems (DSS), or executive support systems (ESS), and user interfaces. There are six analytical functions provided by BI systems to achieve these goals: predefined production reports, parameter-driven reports, dashboards and scorecards, ad hoc queries and searches, drill-down capabilities, and the ability to model scenarios and make forecasts.
Business Intelligence Users
Business analytics enables various types of exploration and predictive modeling compared to BI tools. Business analytics focuses on transforming raw or messy information into knowledge, and knowledge into business value. It further extends to predicting the most likely scenarios. While there is overlap between business analytics and business intelligence, analytics is increasingly used to describe statistical and mathematical analysis that breaks down, categorizes, or scores data to predict the most likely scenarios. While business intelligence is more concerned with providing historical data analysis, business analytics is more directed towards predictive capabilities.
The process involved in business analytics includes data modeling, analyzing possible scenarios, and presenting the best options to address those scenarios. These tools can be used on various types of data and do not rely on databases with cleaned and formatted data. The financial services industry is one that heavily invests in data analytics due to its future-oriented nature.
Business analytics works by setting business analysis goals, selecting the analysis methodology, and obtaining data to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration into a repository such as a data warehouse or data mart. Initial analysis is typically performed on smaller sample sets of data. Analytical tools range from spreadsheets with statistical functions to complex data mining and predictive modeling applications. When patterns and relationships within the data are revealed, new questions are asked, and the analytical process is repeated until business goals are met.
The application of predictive models involves assessing data records—typically within a database—and using scores to optimize real-time decisions within applications and business processes. BA also supports tactical decision-making in response to unforeseen events. In many cases, decision-making is automated to support real-time responsiveness.
While there is overlap between business intelligence and business analytics, both can provide business value in most industries. Both types of tools are important for many companies, and many CIOs embrace both due to their different strengths. A December 2013 press release from Gartner stated that the gap between business intelligence and business analytics is expected to narrow in the coming years, and by 2016, as big data matures and becomes more familiar, these types of tools will work even more closely together.
Business intelligence and business analytics help companies adapt more quickly to customer needs, whether through increased availability of goods or empowering sales personnel with new approaches. As big data becomes more important, companies are expected to invest in better end-user training for business intelligence and analytics tools to create a culture that encourages data exploration and fact-based decision-making. At the same time, vendors are creating user-friendly tools and offering services that free IT teams from much of the coding required for big data analytics.
In conclusion, business intelligence and business analytics are essential for supporting decision-making in organizations. While BI focuses on historical data analysis and providing insights into past and present trends, BA goes beyond that by leveraging various data sources and advanced tools to predict future scenarios. Both approaches have their unique strengths and contribute to the overall success of businesses. As the availability of data continues to grow and technology advances, the convergence of BI and BA is expected to increase, enabling organizations to make more informed and proactive decisions based on accurate and timely information.