Unlocking the power of data can enable organizations to discover trends that help increase speed to insights, inform better decision making and provide a quantifiable foundation for defining business goals. In addition, combining automation with data analytics can minimize time spent on data prep and other manual tasks. However, many employees need more digital skills to wrangle big data and unlock its potential.
Data analytics upskilling has been a long time coming. More than ever, upskilling is top-of-mind for many companies, with 74% of CEOs reporting that lack of key skills is a major concern, especially as 75% of CEOs believe the transition toward automation will continue.
Among the wide range of skills and knowledge, the ability to understand data and use the insights gained from analytics has been in high demand. But to upskill in data analytics, learning professionals need a holistic approach that offers hands-on learning that sticks and scales.
Table of Contents
Why is upskilling important?
Common trends driving the need to upskill Data Analytics skills
How do I upskill myself as a Data Analyst?
Key takeaways
Why is upskilling important?
According to the World Economic Forum (WEF) 2018 Future of Jobs Report, the Fourth Industrial Revolution will create roughly 133 million new jobs by 2022. Concurrently, 75 million jobs will be obsolete in the large enterprise sector alone.
Several employees who lack new skills, including in data analytics, are at a high risk of being displaced.
Many experts and global organizations say that “Industry 4.0” is finally here. And this revolution involves accelerating, ongoing digital changes, including automation, AI and digitization, new disruptive business models, and enhancing business complexity.
These business changes lead to a great transformation in both the nature and type of jobs and the structure of the workforce. This technological transformation impacts the entire workforce, from low-skilled jobs to advanced roles with high expertise. Current job occupations need new skill sets.
In WEF’s most recent future of jobs reports, including the 2020’s Jobs of Tomorrow: Mapping Opportunity in the New Economy, it determined that the new labor market is driven to a large degree by advances in data science and AI. This will create a significant number of new jobs in the future.
It’s important to understand that most of these fast-growing job categories, including marketing and content, sales, people and culture, and the Green economy, are shifting towards a greater data and analytics focus.
For example, Pathstream’s upskilling course, Digital Marketing, teaches vital skills such as marketing analytics and fundamental data analysis. While Digital Marketing jobs fall under the Marketing, Sales, and Content job cluster, they still need analytical skills.
In general, the new job opportunities that need data analytics are increasingly becoming more widespread than just the data and artificial intelligence field. In reality, nearly 2 million new jobs in other job categories identified by WEF are impacted by analytics.
Common trends driving the need to upskill Data Analytics skills
With the advancements in digital transformation and technology being at the forefront of strategic initiatives, there is increasing demand for tech-savvy, data-specific job roles for most employees within an organization. The global pandemic has further sped this transformation.
Additionally, with technology heavily driving the way companies are run, the need to upskill data science competence is rapidly increasing. Now and in the future, professionals need to be aware of these trends to help them future-proof their skills to be more attractive and competitive.
Below are some of the trends that drive the need for upskilling and reskilling in data analytics:
1. Data analytics is universal
Over the last decade, data was largely considered a by-product of digital platforms and applications. Organizations focused primarily on cleaning, storing, and managing big data securely.
Today, companies focus on data as an enterprise-wide asset that must be broken down and refined using data science and analytics for profits. However, the volume of available data is rapidly increasing, so organizations will need more employees with data skills to profit continuously from the pervasive volumes of data.
2. Artificial Intelligence (AI)
Artificial intelligence is a significant factor driving the need to upskill data analytics skills. AI is replacing a large part of the workforce and has become an integral part of the corporate business units as well as functional strategy and operations.
With AI and machine learning, systems are becoming smarter and achieving more daily. The potential for artificial intelligence to automate repetitive and mundane tasks means a huge shift in the workforce. While there’s concern about workforce displacement, several opportunities are created for employees to move to higher-level roles.
3. Data-driven performance
Organizations and employees continue to fall behind on performance as the skills needed to understand big data and the positive impact that data contributes need to catch up. High-performing organizations dedicate at least 20% of their EBITA to data analytics. In addition, the gap in performance between organizations with data-driven teams and those lacking data skills grows wider each year. Data analytics upskilling helps employees understand and interpret data leading to a sustainable future.
4. Skills gap and talent shortage
A McKinsey survey reports that data analytics is the greatest skill gap noted through organizations. 40% of organizations confirm that it is a significant priority and crucial for overall business success to upskill these gaps.
Furthermore, while companies are trying to become more data-driven, data science and analytics efforts are being held back by a data talent shortage. A combination of factors impacts the deficit: high salary demands, a hyper-competitive market, or a prolonged period to fill data-related roles. The result is that demand for data analytics talent outruns supply. Upskilling and reskilling can help organizations build an internal pool of necessary talent and make them less dependent on costly, hard-to-hire talent.
5. The bottom-line cost
The WEF reports that the average cost of hiring and onboarding new employees is roughly $4,425. On the other hand, data from the Association for Talent Development reports that the average cost of upskilling existing talent is just $1,300. Even if the figure is doubled to cover the technical complexity of data skills, organizations find upskilling existing employees much more cost-effective than hiring new talent. And with data skillsets come better salaries.
6. Cross-functional teams
Data science and analytics are now considered a team sport. To achieve data-driven objectives and incorporate the diversity of skills that teams require, these data project teams must be cross-functional. This combines teams working toward similar goals.
How do I upskill myself as a Data Analyst?
As the demand for data skills increases and skill gaps and talent shortages continue, it is important to upskill now. But how do you start? Here are a few ways to upskill as a data analyst.
Become proficient in new technical tool sets
Solid technical toolsets are becoming increasingly important, and this isn’t changing any time soon. Even though computers have become easier to use in several ways, the leading edge is still more complicated than ever. This complexity often scares many employees away from developing their technical toolsets, but the benefits are great.
Having diverse skills, culture, and education and keeping up with ongoing and changing job role dynamics is important.
Learning to enhance one’s technical skills is a worthwhile investment. As the world becomes more data concentrated and complex, it will become even more crucial for analysts to have more than just Excel in their tech stack and toolset for working with and managing data.
Master BI tools
Every organization reaches the point where they require a business intelligence (BI) tool to help them manage and visualize the data to drive analysis and decision-making.
BI tools help eliminate the need for guesswork. They enable data analysts to provide real-time, hyper-accurate reports and assist organizations in understanding the information better.
Predict future trends and stay ahead of the curve
Business leaders and employees need to adopt a selective approach to data analytics upskilling and consider forecasting to obtain a reliable idea of the nature and type of skills and the number of employees needed to accelerate future business goals.
Consider the overall organization needs, the new skill potential that would fit existing talent gaps, and prospective future investments in new tools and technologies that will require new capabilities and talent.
Learn a new programming language or framework
In your journey to upskill your data science ad n analytics skills, you need to become a master of programming languages like Java, Python, R, Scala, etc. And once you feel confident enough in one programming language, you can start mastering another.
Key takeaways
Harnessing the power of data science and analysis arms you with the tools and insights to drive valuable business decisions and efficiencies. Upskilling in ways that enable you to contribute to digital transformation can create a lasting impact and achieve a significant return on your investment.
The ability to make data-driven business decisions is and will continue to be a key competence. Committing to upskilling programs can help you position yourself for success.
With powerful industry-leading digital platforms, you can learn and grow your abilities and see the benefits of upskilling faster. We offer top-of-the-line upskilling opportunities aligned with your professional and personal goals. Aligning individual learning with overall career goals equips you with the skills that support growth. Learning experiences like those offered through Pathstream are learner-centric and enable you to perform at your highest level, empowering you to transform your entire career. Request a demo or check out our programs to learn more.
Was this helpful?
Thanks! What made it helpful?
How could we improve this post?
