What is Forecasting in Data Analytics?

Forecasting is the process of using historical data to make informed predictions about future events. It's a blend of science and art, where data-driven insights are combined with business acumen to forecast what might happen in the future. For example, an e-commerce company might use forecasting to predict customer buying patterns during the holiday season.

This forward-looking approach is essential for strategic planning, resource allocation, and staying ahead in a competitive market.




Contrast with Other Skill:
While reporting the present involves analyzing current data to understand what is happening now, and root cause analysis digs into past data to understand why something happened, forecasting looks towards the future. It's not just about understanding the past or present; it’s about using that information to predict future trends. For instance, while root cause analysis might explain a sudden spike in website traffic, forecasting would use that data to predict future spikes.

It leverages patterns, trends, and relationships identified in historical data to predict what could happen next. This predictive capability is what sets it apart from other data analysis tasks.




Common Forecasting Techniques:
In this skilleton, we will explore several common forecasting techniques that are essential for internet businesses. These include:

  • - Moving Average: A method used to smooth out short-term fluctuations and highlight longer-term trends in data. For example, a gaming company may use moving averages to understand the changing preferences of its player base over time.

  • - Linear Regression: A statistical technique for understanding the relationship between variables and predicting future outcomes. An ed-tech firm might use linear regression to predict user engagement based on historical usage patterns.

  • - Simple Time Series Models: Approaches like ARIMA (AutoRegressive Integrated Moving Average) that analyze time-based data to forecast future points. This could be used by a fintech company to forecast stock market trends.

Each of these techniques offers unique insights and applications, and we will delve into how to apply them effectively in subsequent concepts.