Featured Post

SQL Query: 3 Methods for Calculating Cumulative SUM

Image
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

Data Analytics Tutorial for COBOL Programmers

Mainframe developers look for an alternative IT course to grow in their careers. I have explained in this post how can they use their business knowledge. Data analytics tutorial is a top an alternative for COBOL programmers.

analytics tutorial for COBOL developers

What is Data Analytics

The field of data science is evolving into one of the fastest-growing and most in-demand fields in the world. 

Organizations across industries are looking to make sense of the data they can now collect from new technologies – from predicting the next hot product to determining the risk of an infectious disease outbreak.

Demand and Opportunity

  • According to The New York Times, data science “promises to revolutionize industries from business to government, health care to academia.”
  • As data accumulates, organizations are hiring individuals with the expertise to find meaning in the numbers and drive positive business decisions based on what they learn.
  • It is estimated that by 2018, 4 million to 5 million jobs in the United States will require data analysis skills, and a recent study from the McKinsey Global Institute found “a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.).”
  • Based on the number of job openings, median base salary and career opportunities, Glassdoor has ranked data scientist as the “Best Job in America”.

Who can opt for Data Analytics Tutorial

  1. Strong interest in data science 
  2. Background in intro level statistics 
  3. Programming experience in Python for Data Science 
  4. Understanding of programming concepts such as variables, functions, loops, and basic python data structures like lists and dictionaries
Start Your Free Data analytics Tutorial here.

Comments

Popular posts from this blog

How to Fix datetime Import Error in Python Quickly

Explained Ideal Structure of Python Class

How to Check Kafka Available Brokers