About Dataset

Context

Analytics refers to the methodical examination and calculation of data or statistics. Its purpose is to uncover, interpret, and convey meaningful patterns found within the data. Additionally, analytics involves utilizing these data patterns to make informed decisions. It proves valuable in domains abundant with recorded information, employing a combination of statistics, computer programming, and operations research to measure performance.

Businesses can leverage analytics to describe, predict, and enhance their overall performance. Various branches of analytics encompass predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, Big Data Analytics, retail analytics, supply chain analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, graph analytics, credit risk analysis, and fraud analytics. Due to the extensive computational requirements involved (particularly with big data), analytics algorithms and software utilize state-of-the-art methods from computer science, statistics, and mathematics.

Data Dictionary

Content

This Dataset contains information of 22700+ Software Professionals with different features like their Salaries (₹), Name of the Company, Company Rating, Number of times Salaries Reported, and Location of the Company.

Extra Features Added: 1. Employment Status 2. Job Roles

Acknowledgements

This Dataset is created from https://www.glassdoor.co.in/. If you want to learn more, you can visit the Website.

Roles Included:

Android Developer Android Developer - Intern Android Developer - Contractor Android Developer Contractor Senior Android Developer Android Software Engineer Android Engineer Android Applications Developer - Intern Android Applications Developer Android App Developer - Intern Senior Android Developer and Team Lead Android Tech Lead Product Engineer (Android) Software Engineer - Android Android Software Developer Android Software Developer - Intern Senior Android Developer Contractor Junior Android Developer - Intern Junior Android Developer Android Applications Developer - Contractor Android App Developer Lead Android Developer Android Engineer - Intern Sr. Android Developer Senior Android Engineer Senior Software Engineer - Android Android - Intern Android Android & Flutter Developer - Intern Associate Android Developer Senior Android Applications Developer Android Developer Trainee Sr Android developer Android Trainee Android Trainee - Intern Trainee Android Developer Android Lead Android Lead Developer Android Development - Intern Android Development Android Team Lead Senior, Android Developer Lead Android Engineer Tech Lead- Android Applications Developer Senior Android Software Developer Full Stack Android Developer Android Framework Developer Android Architect Android & Flutter Developer Senior Software Engineer, Android Android App Development Sr Android Engineer Android Team Leader Android Technical Lead SDE2(Android) Web Developer/Android Developer - Intern Android Applications Develpoers Android Platform Developer - Intern Android Test Engineer Senior Engineer - Android Android Framework Engineer Game Developer ( Android, Windows) Android Testing Senior Software Engineer (Android/Mobility) Ace - Android Development Software Developer (Android) - Intern Android Mobile Developer Android and Flutt...

Senior Executive was the highest-earning software development job worldwide as of 2024, with the average annual salary amounting to around *** thousand U.S. dollars. Developer advocate and engineering manager were the other developer jobs with high salaries. Software developer A software developer, or more commonly known as a programmer or a coder, is a person who creates software by using computer languages. There are two main types of software developers: application developer – those who design computer or mobile applications – and system developer – those who focus on operating systems-level software and network distribution software. In 2021, there were around **** million software developers worldwide. Programming languages A programming language is a formal language that instruct a computer or computing device to perform certain tasks. Languages that software developers use to write code are called “high-level languages”; these can be complied into a “low-level language” which can be understood by the computer hardware. Programming languages that are most used by developers include JavaScript, HTML/CSS, SQL, and Python. Clojure, F# and Elixir, on the other hand, are the languages associated with the highest salaries.

According to the survey, Erlang and Elixir are the programming languages that are associated with the highest salaries worldwide in 2024, with an average of around *** and ** thousand U.S. dollars respectively.

Graph and download economic data for Employed full time: Wage and salary workers: Computer programmers occupations: 16 years and over (LEU0254477100A) from 2000 to 2024 about computers, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

This dataset merges player per-game and advanced statistics for the NBA's 2022-23 season with player salary data, creating a comprehensive resource for understanding the performance and financial aspects of professional basketball players. The dataset is the result of web scraping player salary information from Hoopshype, and downloading traditional per-game and advanced statistics from Basketball Reference.

Key Features:

• Player Information: Player name, team(s) played for during the season.
• Per Game Statistics: A wide array of per-game statistics, including points scored (PPG), assists (APG), rebounds (RPG), steals (SPG), blocks (BPG), and more.
• Shooting Efficiency: Metrics like field goal percentage (FG%), three-point percentage (3P%), two-point percentage (2P%), and free throw percentage (FT%) for assessing scoring efficiency.
• Advanced Statistics: A wide array of advanced metrics such as value over replacement player (VORP), win shares (WS) and true shooting percentage (TS%)
• Salaries: The financial aspect of the dataset includes player salaries for the 2022-23 season, offering insights into player earning

Potential Uses:

• Player Performance Analysis: Analysts can evaluate player performance in correlation with their earnings, identifying players who provide strong value for their salaries.
• Team Budgeting and Strategy: Teams can use this dataset to assess the financial implications of player acquisitions, trades, and salary cap management.
• Player Earnings Insights: The dataset offers insights into the income distribution of NBA players, helping fans and analysts understand the financial side of professional basketball.
• Data-Driven Decisions: Data scientists can leverage this combined dataset for predictive modeling and machine learning applications, including salary predictions and player valuation.

Acknowledgements: Basketball Reference, Hoopshype

Salary by Profession and Country Over Time

Salary Differences by Country and Profession

By Kelly Garrett [source]

About this dataset

This dataset contains survey responses from 882 data professionals from 46 countries who took part in the 2021 Global Data Professional Salary Survey. Our goal was to understand how much database administrators, data analysts, data architects, developers and data scientists make across the world in 2017-2021.

The survey covers three years of salary trends, allowing you to compare and contrast movements over time. It also includes an optional postal code field which can be used to identify global regions with specific salary trends. In addition, all questions asked this year were also asked in 2017 and 2018 so that you can easily track changes in compensation over three years.

The spreadsheet contains anonymized responses which are provided as public domain making it available for any purpose without attribution or mention of anyone else. With this dataset at your disposal you'll have access to the detailed salary information needed to make informed decisions about your career development!

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Featured Notebooks

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How to use the dataset

• Start by familiarizing yourself with the columns in this dataset. The columns range from age of respondent to country of residence. It also includes salary information for each year (average annual income for 2017, 2018, and 2019). Read through each column header carefully to understand what you're looking at.

• Explore some basic summary statistics about the sample group such as median salary levels by profession or average age by nationality are interesting ways to get acquainted with this data set quickly. Excel's native statistical tools may be used here if you're using an excel file version as your source material; otherwise, you can use any programming language or statistics software that supports importing an exportable CSV (Comma Separated Values) format file or conversion thereof into something manipulable form like a spreadsheet or table structure within your preferred platform..

• You'll then want to identify which factors might be influencing salaries such as experience level, gender and geographical location etc., and attempt some correlation testing between those features against salaries across different job roles or countries over time - where possible without having external datasets available terms of area data points matching up perfectly between thematic dimensions presented within the Respondents' Survey Results tab.. Subsets may also prove relevant when carrying out deeper statistical testing—for example isolating particular participation sets like Ireland alone versus looking at just Europe/Middle East/Africa region altogether..

• Finally look at how these factors have changed over time - it's worth bearing in mind that seasonality might play a role here too depending on where respondents originally reside so it could still be relevant if larger trends towards comparing yearly cohorts differs more widely than expected based purely national economic condition context changes during particular quarters throughout those periods tracked in our findings report � comparison purposes if looking country-by-country instead just individual profiles without taking overall stimulant effects into account e.g higher education qualifications among ~2 yr cohorts vs ~3 yr ones across different populations: Comparing annual amounts doled out employers making ultra-quick transitioning easier tracking changes alone isn't feasible because they're normalized

Research Ideas

• Analyzing regional salary gaps amongst data professionals within the same country, or between countries.
• Evaluating trends in salary rates over time by reviewing changes in year over year responses.
• Generating employer profiles by comparing the salary range of employees at different organizations and industries, as well storing demographic info of individuals who participated in the survey (i.e age range, gender etc)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: 2019_Data_Professional_Salary_Survey_Responses.csv

File: Data_Professional_Salary_Survey_Responses.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Kelly Garrett.

According to a report released in July 2020 in Vietnam, tech management positions such as chief technology officer (CTO) or chief information officer (CIO) had the highest average salary per month. People in this position usually earned around ***** U.S. dollars monthly. The second highest-paid position was technical director/ engineering manager with an average salary of ***** U.S. dollars per month. Bridge system engineer stood at the bottom of the top 10, earning close to ***** U.S. dollars monthly on average.

About Dataset

Context

Analytics refers to the methodical examination and calculation of data or statistics. Its purpose is to uncover, interpret, and convey meaningful patterns found within the data. Additionally, analytics involves utilizing these data patterns to make informed decisions. It proves valuable in domains abundant with recorded information, employing a combination of statistics, computer programming, and operations research to measure performance.

Businesses can leverage analytics to describe, predict, and enhance their overall performance. Various branches of analytics encompass predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, Big Data Analytics, retail analytics, supply chain analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, graph analytics, credit risk analysis, and fraud analytics. Due to the extensive computational requirements involved (particularly with big data), analytics algorithms and software utilize state-of-the-art methods from computer science, statistics, and mathematics.

Data Dictionary

Content

This Dataset consists of salaries for Data Scientists, Machine Learning Engineers, Data Analysts, and Data Engineers in various cities across India (2022).

-Salary Dataset.csv -Partially Cleaned Salary Dataset.csv

Acknowledgements

This Dataset is created from https://www.glassdoor.co.in/. If you want to learn more, you can visit the Website.

In 2023, Polish programmers who specialized in embedded programming and were hired on an employment contract earned the most, at ***** zloty net per month.

Graph and download economic data for Employed full time: Wage and salary workers: Computer programmers occupations: 16 years and over: Women (LEU0254690700A) from 2000 to 2024 about computers, occupation, full-time, females, salaries, workers, 16 years +, wages, employment, and USA.

This Dataset containes the details of the AI, ML, Data Science Salary (2020- 2025). Salary data is in USD and recalculated at its average fx rate during the year for salaries entered in other currencies.

The data is processed and updated on a weekly basis so the rankings may change over time during the year.

Attribute Information

• work_year: The year the salary was paid.
• experience_level: The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director
• employment_type: The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance
• job_title: The role worked in during the year.
• salary: The total gross salary amount paid.
• salary_currency: The currency of the salary paid as an ISO 4217 currency code.
• salary_in_usd: The salary in USD (FX rate divided by avg. USD rate of respective year) via statistical data from the BIS and central banks.
• employee_residence: Employee's primary country of residence in during the work year as an ISO 3166 country code.
• remote_ratio : The overall amount of work done remotely, possible values are as follows: 0 No remote work (less than 20%) 50 Partially remote/hybird 100 Fully remote (more than 80%)
• company_location: The country of the employer's main office or contracting branch as an ISO 3166 country code.
• company_size: The average number of people that worked for the company during the year: S less than 50 employees (small) M 50 to 250 employees (medium) L more than 250 employees (large)

Acknowledgements

https://aijobs.net/

Photo by Anastassia Anufrieva on Unsplash

Context

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

Organizations may apply analytics to business data to describe, predict, and improve business performance. Specifically, areas within analytics include predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, Big Data Analytics, retail analytics, supply chain analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, graph analytics, credit risk analysis, and fraud analytics. Since analytics can require extensive computation (see big data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics.

Content

This Dataset consists of salaries for Data Scientists, Machine Learning Engineers, Data Analysts, and Data Engineers in various cities across India (2022).

-Salary Dataset.csv -Partially Cleaned Salary Dataset.csv

Structure of the Dataset

https://i.imgur.com/G8GwKx5.png" alt="">

Acknowledgements

This Dataset is created from https://www.glassdoor.co.in/. If you want to learn more, you can visit the Website.

Cover Photo by rupixen.com on Unsplash

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer programmers occupations: 16 years and over: Men (LEU0254637300A) from 2000 to 2024 about second quartile, computers, occupation, full-time, males, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

In 2023, the growth rate of the average salary of a software developer in Russia reached over ** percent in Russian ruble terms. In U.S. dollar terms, the salary declined by more than ***** percent from the previous year.

I took the average salaries of software developers in Turkey for 2025 and used statistical methods to create 1,000 salary data points. I will make improvements to ensure the data is more consistent.

Turkey Wage & Salary Index: TS: IC: Computer Programming data was reported at 230.921 2010=100 in Dec 2017. This records an increase from the previous number of 222.158 2010=100 for Sep 2017. Turkey Wage & Salary Index: TS: IC: Computer Programming data is updated quarterly, averaging 109.719 2010=100 from Mar 2005 (Median) to Dec 2017, with 52 observations. The data reached an all-time high of 230.921 2010=100 in Dec 2017 and a record low of 34.823 2010=100 in Mar 2005. Turkey Wage & Salary Index: TS: IC: Computer Programming data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.G048: Gross Wage and Salary Index: NACE Rev 2: 2010=100: by Trade and Services. Rebased from 2010=100 to 2015=100 Replacement series ID: 403908797

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer programmers occupations: 16 years and over: Women (LEU0254744100A) from 2000 to 2024 about second quartile, computers, occupation, full-time, females, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

Graph and download economic data for Employed full time: Wage and salary workers: Software developers, applications and systems software occupations: 16 years and over (LEU0254477200A) from 2000 to 2019 about software, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

The statistic shows the global developer salary expectations of software developers compared to market values, as of early 2017. According to the survey, many developers (**** percent) reported that they felt somewhat underpaid compared to their market value, while **** percent reported that they were neither underpaid nor overpaid. Only *** percent of respondents reported that they believed they were somewhat overpaid.

This statistic displays the programmer analyst salary in Italy in 2016, broken down by gender. According to data, the highest salary was among male programmer analyst who are also managers, with an average income of ****** euros per year. Female employed programmer analyst earned an average of ****** euros per year, ** euros less of their male correspondents.