The top data skills for 2023 are business intelligence and data engineering, ESG reporting, financial data, and AI. As 2022 draws to a close, many data professionals will wonder where they should focus their attention next year and where the opportunities are. What new area or skill is worth investing my time in?
The good thing is that many critical data skills, such as BI and data engineering, will be needed more than ever in 2023.
We touch on these skills first and why we see them as important. We then turn our attention to the emerging area of ESG. Following that we examine Financial data and lastly AI.
Table of contents
Business Intelligence (BI)
Business Intelligence or BI or reporting, no matter what you want to call it, continues to grow rapidly. Businesses are always evolving and adapting to new market conditions. To support decision-making, BI and reporting will be needed more than ever.
Microsoft’s Power BI is the clear leading BI tool in the market today. Don’t just discount it as being a easy tool that anyone can use. Don’t get me wrong, it is. But to implement it correctly at an enterprise scale requires the right skills. There is a real opportunity for some who can design and architect Power BI at an enterprise level.
Check out our article if you are unsure what skills are needed for business intelligence.
Data Engineering
Organisations continue to build new data warehouses and data lakes to meet the ever-increasing demand for data. As technology and business continue to evolve, this trend will continue. Data engineering skills are needed to build and advance these data platforms.
In addition to the core systems businesses use and extract data from, the usage of point solutions has proliferated. Services such as SurveyMonkey and Mailchimp are examples of this. Companies use these services and then need to analyse the output with their operational data. This requires data engineering skills to integrate into their existing reporting and BI platform.
We’ve put together a detailed breakdown of the skills required for data engineering.
Domain Specific Skills
Here we picked three domain specific data skills we at the Data Knowledge Club believe will be go from strength to strength in 2023.
ESG
ESG stands for Environment, Social and Governance and is one of the hottest topics in business today. Companies must prove they are carrying out activities in an environmentally friendly way. They need to be socially conscious, meaning they must responsibly manage the human aspect of their business and the communities they operate in. Lastly, Governance relates to how the organisation is managed transparently and ethically.
ESG is becoming extremely important; investors decide to invest in companies based on a company’s ESG metrics. Individuals choose whether the company they want to work for aligns with their beliefs based on how a company meets ESG standards.
ESG reporting has been around in the investment world for a while, but now it is becoming a requirement for publicly listed companies. Various standard bodies are currently developing several ESG standards. Many of these are still in flux, meaning companies comply with more than one standard.
ESG is a big opportunity for data professionals
Companies must legally comply with these reporting standards, meaning they must invest in capturing and reporting on the data needed. Often, vast data sets must be processed with complex calculations to calculate specific ESG metrics.
A big opportunity for data professionals is ESG. Technology and data expertise enable the reporting of ESG data. The Data Knowledge Club views ESG as a significant growth area for 2023. If you are environmentally conscious, working as an ESG data specialist could be a great rewarding career path due to the increased demand for ESG reporting.
Financial
Financial data has always been a great area to specialise in because its a core function of every organisation. With the economic conditions changing globally this year, much more focus will be on the financial performance of companies. Companies are now paying much closer attention to their financial data.
All companies will look to analyse their costs. For example, spend analytics has become much more popular as organisations seek to ensure they can adequately manage their spending.
Increasingly, finance departments are taking a more active role in business operations and becoming more data-driven. Since the pandemic, companies must model financial scenarios far better to react faster to market conditions changing. This leads to a need for blending financial, operational, and external data sources.
Additionally, large financial transformations are topical as businesses seek to benefit from adopting the latest financial planning and analysis tools.
All of the above indicates that there will be a lot of opportunities for data professionals over the next few years working with finance departments as companies pay closer attention to their financial data and undertake financial transformation projects.
AI
AI and machine learning will continue to mature in the next few years, creating countless opportunities for data professionals. However, it can be hard to keep up with the developments and emerging new areas in AI. Attempting to pick a topic to skill up on that won’t go out of date quickly is an art.
Understanding statistical learning (machine learning models that learn from data) is a great place to start your AI journey. As part of this, you will become familiar with two core concepts, classification and regression. These topics might sound daunting at first, but they are the techniques used for marketing segmentation (classification) and forecasting (regression).
Our recommendation, if you are new to the field of AI or machine learning, is to focus on the basics first. Understanding the core fundamentals will set you up to deepen your knowledge in AI and to specialise further.
We’ve put together a breakdown of the most important skills you need as a data scientist.
Conclusion
There will always be specific data skills that are always in high demand such as BI and data engineering. In addition, to these skills nowadays, it can be very advantageous to one’s career to specialise in a domain. ESG, is an area that is rapidly growing and driven by standards. Financial data expertise becomes even more important with the financial pressures on businesses. AI will continue to evolve and great a demand for new data skills. These will create countless opportunities for anyone who builds expertise in these areas.
We hope you enjoyed the top data skills for 2023. We will update these as we move through 2023.
We really like to get feedback from our readers or ideas of topics you would like us to cover.
