Data Analytics Insights

From Novice To Data Hero: Top Resources For Becoming A Citizen Data Scientist

It is estimated that 90% of the world's data was generated in the last two years alone (Sources: Statista, Bernard Marr & Co.) This figure has increased by an estimated 74x from just 2 zettabytes (2 bn GBs) in 2010 to 129 zettabytes (140 bn GBs) in 2023. Yes, that is a HUGE number!

NC
Neelam Chakrabarty
September 17, 2024
7 min read
Updated September 18, 2024
From Novice To Data Hero: Top Resources For Becoming A Citizen Data Scientist

It is estimated that 90% of the world's data was generated in the last two years alone (Sources: Statista, Bernard Marr & Co.) This figure has increased by an estimated 74x from just 2 zettabytes (2 bn GBs) in 2010 to 129 zettabytes (140 bn GBs) in 2023. Yes, that is a HUGE number!

With that much data being generated, data literacy has become an essential skill, empowering individuals to navigate, interpret, and harness this vast sea of information for informed decision-making and to protect their digital footprint in an increasingly data-driven world.

But First, What is a Citizen Data Scientist

This is a 2-part blog series on the topic of Citizen Data Scientist. In part 1, we discussed in detail the emergence of this relatively new role in many large organizations, the genesis behind this trend, the challenges this role faces, etc.

Citizen Data Scientist = Business expert + Data Scientist - PhD. degree in data

The Decentralization of Data Expertise

Data is rapidly becoming a universal artifact in every team across organizations. There's a growing trend of data teams becoming decentralized, with each functional team requiring its own data expert. These experts possess the skills to work with and analyze data for quick decision-making without relying heavily on a centralized data science team. This shift reflects the increasing importance of data literacy across all business functions. As a result, many are taking on the role of citizen data scientists within their teams, bridging the gap between domain expertise and data analysis.

10 Essential Skills Required To Become A Citizen Data Scientist

These skills combine technical proficiency with business knowledge and soft skills, allowing citizen data scientists to bridge the gap between advanced analytics and business operations, even without formal data science training.

  1. $1
  2. $1
  3. $1
  4. $1
  5. $1
  6. $1
  7. $1
  8. $1
  9. $1
  10. $1

Top 10 Online Courses to Develop Your Skills as a Citizen Data Scientist

Top 10 Books to Level Up Your Data Skills

Top 10 Podcasts to Enhance Your Data Knowledge

Top 10 YouTube Channels to Learn Visually

  1. $1
  2. $1
  3. $1
  4. $1
  5. $1
  6. $1
  7. $1
  8. $1
  9. $1
  10. $1

Top 5 Data Science Communities

Kaggle
Kaggle is a well-known platform for data science competitions, where users can share datasets, explore machine learning models, and participate in challenges. It offers a supportive community for both beginners and experienced data scientists.

Reddit
Reddit hosts several active subreddits focused on data science, such as r/datascience, r/machinelearning, and r/dataisbeautiful. These communities provide a platform for discussions, sharing resources, and seeking advice from peers.

IBM Data Science Community
This community offers expert insights, discussions, and resources related to data science challenges. It's a great place to connect with industry professionals and stay updated on the latest trends.

Data Science Central
Data Science Central is one of the largest online communities for data scientists. It features forums, blogs, and articles, making it a valuable resource for networking and learning about industry trends.

Open Data Science
This community focuses on collaboration among data scientists, engineers, and students. It offers a variety of resources, including articles, tutorials, and events, fostering an inclusive environment for learning and sharing.

Tools of the Trade

While there are dozens of tools available to data professionals, we have filtered the list to show the most popular ones based on their use, ease of use, cost, and skill level required:

Category Tool Ease of Use (1 Most Difficult - 5 Easiest) Cost ($/year) Skill Level
Cleaning OpenRefine 4 Free Beginner
Cleaning Trifacta 3 (5,000-50,000) Intermediate
Cleaning Talend 3 (1,000-200,000) Intermediate
Cleaning Alteryx 2 (5,200-80,000) Advanced
Cleaning Dataiku 3 (20,000-200,000) Intermediate
Analysis Excel 3 (70-160) Beginner
Analysis R 2 Free Advanced
Analysis Python 3 Free Intermediate
Analysis SAS 2 (8,000-210,000) Expert
Analysis SPSS 3 (1,200-7,500) Intermediate
Visualization Tableau 4 (70-840) Intermediate
Visualization Power BI 4 (120-9,000) Intermediate
Visualization QlikView 3 (1,500-35,000) Advanced
Visualization Looker 3 (3,000-5,000) Intermediate
Visualization D3.js 1 Free Expert
Cleaning, Analysis, Visualization Querri 5 (900+) Beginner

Note:

  • Ease of Use is rated on a scale of 1-5, with 5 being the easiest to use.
  • Cost is given as a range (min-max) or average per year in USD. Some tools have wide ranges due to different editions or licensing models.
  • Skill Level is categorized as Novice, Intermediate, Advanced, or Expert.
  • These rankings are subjective and may vary based on individual experiences and specific use cases.

As organizations shift towards a decentralized model of data expertise, the role of citizen data scientists is becoming increasingly vital. This is where tools like Querri come into play. Designed to empower users with minimal technical background, Querri allows team members to extract insights from data seamlessly. By leveraging such intuitive tools, teams can enhance their decision-making processes without relying solely on specialized data teams.

If you would like to try out Querri, sign up for the free trial (no credit card required).

Tags

#Data Analytics

Share this article

Ready to unlock your data's potential?

Turn raw data into decisions in minutes