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Thursday, 15 September, 2022

State of data science 2022 report analysis

Data science technologies, techniques and tools change weekly. Every day, we are seeing huge data increases and the importance of extracting the right value at the right time. This report is a good indication of the state of play of data science today. It covers data science tools, approach, location, production, skills and more.  I have highlighted the main points, key stats, and key insights.

The report is ideal for
This report is ideal for anyone involved in data and want to understand the data landscape.

  • Particular interest for CTOs, CIO’s, DevOps, Data engineers and data teams

Main points

  • Security – Many companies are scaling back on open-source technology because of security concerns in the past year
  • Skills – Many companies are worried about the skills shortage in data science, and it is one of the most significant barriers to entering this space
  • Retention – Companies will have to look at ways of attracting and retaining a skilled workforce
  • Bias – Bias and ethical data science are still a big concern and promising to address
  • Future – Want to see more development in open-source technology this coming year

Key stats

  • Data preparation: 22% of time spent on data preparation
  • Open source: 32% Want to see further innovation in the open-source science community
  • Platforms: 28% are using AWS Sagemaker
  • Platforms: 27% are using Azure, Databricks
  • Platforms: 26% are using Google BigQuery, Snowflake, DataRobot
  • Data collection: 31% evaluate data collection methods according to internally set standards
  • Models: 35% perform a series of controlled tests to assess model interpretability
  • On-prem: 41% deploy models (in production) on-premises servers
  • Roadblocks: 34% cite meeting IT standards as the major roadblock
  • Skills gap: 38% say that there are engineering skills gaps
  • Open-source: 87% of enterprises use open-source software
  • Top language: 31% of respondents use python always
  • Job satisfaction: 36% are moderately satisfied with their job
  • Skills concern: 64% are concerned with the ability to recruit/retain technical talent
  • Talent shortage: 44% train employees to bypass skills shortage
  • Lots more…

Takeaways and insights – Managers 
The report is fascinating as the data science landscape is buoyant, and healthy with an air of optimism for the future. It highlights the need to keep the data science team engaged in the business and involved in the digital strategy. It highlights the importance of increasing skills with training. A result of this can reduce skills shortages, fuel innovation and increase retention for the future.

There seems to be a huge proportion of companies using open-source technology; however many are concerned with risk. Doing a complete audit/risk assessment may trap issues early. Also, addressing data governance and ethics will help reduce the risk of exposure and strengthen operations throughout the organisation.

Takeaways and insights – Engineers/DataOps, data teams
The data science landscape is exciting, with lots of learning and growth opportunities. Many companies are using a vast range of tools and platforms and considering more. As tools constantly evolve, keep an eye on all the tools, platforms and possibilities. If your team is short in skills, investing in long-term training and creating a skills bank strategy may be suitable.

Governance and ethics is a rising concerns. It would be best to address this as early as possible. This will reduce risk and give your team the confidence to grow and explore new opportunities.


Great report by Anaconda and well worth a read. Click here for the FREE report. (It may ask you for your information)

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