Business Intelligence: Data Mining Techniques

Data Mining

• Data mining is the process of examining large data sets to identify patterns that can help in further analysis.
• E-commerce platforms use data mining to establish correlations between customer demographics, such as gender, age, and preferences, to personalize recommendations and marketing messages.
• Data mining is suitable for fields that rely on transactional data, such as retail, finance, healthcare, and hospitality.

Data Visualization and Reporting

• Dashboarding and visualization tools enable users to access real-time insights and observe trends.
• Ready-made templates with industry-standard metrics can generate customized reports easily.
• These tools eliminate the need for a skilled data professional to draw insights from the data.
• Visualization capabilities bring to light insights that numbers don't.
• Reporting tools provide concise summaries and reports to monitor business performance, such as employee information, sales figures, and expense details.

Performance Management

• Performance management involves tracking progress against pre-determined goals and objectives within defined timeframes.
• BI techniques help companies monitor current progress, predict future trends, and make informed data-driven decisions.
• BI can analyze past sales data to suggest realistic sales targets, helping plan the current budget and predict future scenarios.

Benchmarking

• Benchmarking compares an organization's performance metrics, practices, and processes with those of its competitors or industry peers.
• Companies must align their metrics with industry benchmarks to stay competitive.
• BI can track metrics such as financial metrics, operational efficiency, customer satisfaction, and product quality.

Improving Sales

• BI tools utilize high volumes of customer data to identify customers with high-conversion potential segments.
• Customer data includes customer demographics, customer behavior, customer conversion rates, and other customer metrics.
• Advanced analytics enable accurate sales forecasts, helping companies optimize their selling strategies and timing.
• BI software tracks the effect of marketing campaigns, enabling the marketing team to get better insights and tweak their marketing strategies.

Advanced Statistical Analysis

• Advanced statistical analysis helps in predictive modeling based on multiple factors.
• It uses complex computations to establish relationships between various parameters and reveal trends that help decision-making in business.
• Companies can improve operational efficiency, build better customer targeting and service strategies, and identify new business opportunities by studying trends and patterns.

Data Warehousing

• Data warehousing helps collect and store data from various sources in a centralized database.
• Data warehouses are usually expansive and scalable, keeping the data ready for further analysis and extraction of insights.
• A great application of data warehousing is in the airline industry, where it enables airline operators to predict future demand, make decisions, and standardize processes.