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SQL Query: 3 Methods for Calculating Cumulative SUM

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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.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; 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

7 top initial steps you need before you start HR predictive analytics

Top criteria you need before you start analytics in the Human Resource department. I am sure you need many approvals to start analytics in HR.
hr analytics

The risks involved to start analytics in the Human Resource department

  1. You must comply with the legal requirements in which you operate as it relates to the use of people data. The reason is the analytical insights should reflect the cultural and social marks of your organization.
  2. You need to get involved all stakeholders involved and what the cost of what you're doing is relative to the benefit of doing it.
  3. Use analytics through accountable processes, one of which should be acknowledging that using predictive analytics with the workforce has the potential for negative impact, not just positive impact, Walzer said.
  4. Engage the legal department to make sure you understand any implications before you've done something, not after the fact.
  5. Assess whether the use of analytics involves sensitive areas, which it often will, Walzer said. But, she added, these are often accommodated by using reasonable safeguards.
  6. Know what data you just shouldn't collect. 
  7. One example is prescription drug use of employees. "Many employers have access to it through third-party health care providers, but the idea that you're going to bring it in poses a lot of liability to the organization

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