Business analytics (BA) uses data analysis and statistical methods to solve business problems. It involves exploring an organization's data in a structured and careful way to make better decisions.
Business analytics involves using different methods to analyze data from various sources like sales records, customer information, financial data, and social media interactions. The data can be organized (like in databases or spreadsheets) or unorganized (like emails or social media posts). Analysts use special tools and software to find helpful information from the data.
Here are some key components and techniques involved in business analytics -
- Data collection and aggregation
To make informed decisions, businesses must collect data from surveys, interviews, social media, etc. This data is organized and stored in a central location, like a cloud database, for easy access and analysis.
- Data Mining
Algorithms and statistical models are used in business analytics to uncover hidden patterns and relationships within large data sets. These techniques help to find valuable insights that might not be apparent at first glance.
- Text Mining
Text mining focuses on extracting meaningful information and insights from textual data. It uses various techniques and algorithms to process, analyze, and understand unstructured text data.
- Descriptive Analytics
Include Historical data analysis, a fundamental aspect of business analytics focusing on examining and understanding past performance. It involves analyzing and summarising data from previous events, processes, or activities to identify trends, patterns, and critical insights.
- Predictive Analytics
Forecasting future outcomes and trends based on historical data and statistical models. Predictive models, such as regression and time series analyses, are used to make predictions.
How Business Analytics helps companies make better decisions?
Decisions based on gut instinct or limited data can lead to costly mistakes. With comprehensive data analysis, decision-makers may notice critical factors, trends, or patterns that could significantly impact the outcome of their decisions. Relying on accurate data and analytics helps identify potential risks and opportunities, enabling informed decision-making that reduces the likelihood of costly errors.