Showing posts with the label product analytics

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SQL Query: 3 Methods for Calculating Cumulative SUM

SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON >= GROUP BY, t1.value ORDER BY; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or

Business Vs Demographic Vs Product Analytics

List of top analytics areas and their differences 1. Analytics in Business Advertising Analytics Brand Analytics Promotion Analytics Business-to-business marketing Analytics Social Media Analytics Tracking Studies 2. Demographic Analytics Consumer Analytics Concept Testing Data Mining Customer Satisfaction Study Analytics Demographic Analytics Employee Satisfaction Analysis Text Mining Ethnographic Analytics Media Testing Opinion Polling and Predictive Analytics Usage & Attitude Studies Segmentation Analytics Semiotic and Cultural Analysis 3. Product Analytics Packaging and Design Effectiveness Analytics New Product Development Pricing Studies Product Testing Scenario Planning  Also Read Top IT Skills You Need to Become Data Analyst