As businesses across various industries increasingly rely on data-driven decision making, the challenge of effectively analyzing trends and patterns in data has become more pressing. This course will equip you with the skills and techniques needed to leverage SQL Server tools for trend analysis and forecasting. In this course, Analyzing Trends and Patterns in Data with SQL Server, you’ll gain the ability to derive actionable insights from data to drive informed decision making and strategic planning. First, you’ll explore the fundamental skills and techniques to identify trends in time-series data, and discover the importance of data smoothing techniques in clarifying trends and removing noise or irregularities from datasets. Next, you’ll discover the importance of understanding seasonal variations in data and learn how to detect seasonal patterns using SQL Server tools. Then, you’ll delve into recognizing and interpreting cyclic patterns, gaining insights into recurring patterns that may occur over longer timeframes. Finally, you’ll learn how to leverage SQL Server tools for forecasting models, enabling you to predict future trends and make proactive decisions based on data-driven insights. When you’re finished with this course, you’ll have the skills and knowledge of trend analysis, seasonal and cyclic variations, data smoothing, and forecasting using SQL Server needed to drive data-driven decision making, strategic planning, and operational efficiency in your organization.
Author Name: Amruta Mahajan
Author Description:
Amruta is an experienced Data Analyst with over 12 years of experience in interpreting and analyzing data to drive successful business outcomes. She loves tackling hard problems using data manipulation as her superpower and has worked with market leaders from various fields including Standard & Poors, McDonalds, Mondelez International, General Electric, AMD and Beam Suntory. Amruta is passionate about both teaching and learning and believes “The purpose of life is to discover your gift. The work… more