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How Learning Leaders Can Drive Data Fluency

December 2022
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As we close out the year, the learning agenda has never been more crucial. Organizations around the world are looking at upskilling and reskilling as crucial engines for growth, and data skills are at the forefront of these initiatives.

With that, learning and data leaders are tasked with transforming their workforce’s skills, enabling the next generation of data fluent organizations.

In this webinar, we describe what is exactly a data fluent organization, address all the key data fluency competency areas learning leaders should look to foster, break down the most common data personas for data upskilling and reskilling, and provide practical tips gathered from DataCamp for Business Customers for succeeding with data upskilling initiatives.

Key Takeaways:

  • The data upskilling imperative, and how organizations are addressing the data skill gap

  • The most common personas for data reskilling and upskilling and their needed skills

  • Best practices for succeeding in data upskilling, gathered from DataCamp for Business customers

Summary

In today's data-informed world, businesses are increasingly recognizing the importance of data fluency as a crucial part of digital transformation. With rapid advancements in technology, industries such as finance, hospitality, and retail have been disrupted by data-first companies that utilize data to drive business decisions. As organizations aim to keep pace, they are investing heavily in data science and artificial intelligence initiatives. However, despite these investments, many organizations still find it challenging to build a data-driven culture and face a significant data skills gap. Data fluency, which includes data literacy and the ability to make data-informed decisions, is vital for organizations to thrive. Companies are focusing on upskilling their workforce to bridge this gap, offering personalized learning paths and creating data academies to develop a learning culture.

Key Takeaways:

  • Data fluency is vital for successful digital transformation and business innovation.
  • Organizations face significant challenges in building a data-driven culture.
  • Upskilling employees is necessary to bridge the data skills gap.
  • Learning programs should align with business objectives and be adapted to individual needs.
  • A strong learning culture and data-driven mindset are key to organizational success.

Deep Dives

Data Fluency as a Business Imperative

The disruption witnessed in industries over the past two decades highlights the importance of data fluency as a business imperative. Companies like Airbnb and Amazon have utilized data to innovate and capture significant market share, leading ...
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traditional businesses to invest heavily in data science and AI. However, despite these efforts, many organizations still struggle to utilize the full potential of data. As highlighted by Suleiman Mohanchanderlal, "Data culture isn't simply an option to succeed in data analytics initiatives; it is business critical." For businesses to achieve transformational outcomes, data fluency must be embedded across the organization, enabling data-driven decision-making at all levels.

The Data Skills Gap

The demand for data skills is growing rapidly, yet a significant gap remains between the skills organizations need and those their employees possess. According to McKinsey, 43% of businesses identify data analytics as the most pressing skill gap. This gap poses a serious threat, with many organizations feeling overrun by the need to make data-driven decisions. To address this, companies are increasingly turning to upskilling initiatives. DataCamp's approach, for example, involves creating structured learning paths adapted to different roles and competencies. As Adele noted, "It's vital to align learning paths with both organizational goals and individual career aspirations."

Creating a Learning Culture

A strong learning culture is vital for building data fluency. Organizations must incentivize learning and create environments where employees feel supported in their pursuit of data skills. This involves experimenting with various learning modalities, such as collaborative learning and blended programs that combine online courses with live sessions. For instance, Bloomberg's data analysis with Python program exemplifies a successful blended approach that engages individuals and develops a sense of community. As emphasized by Marcus Robertson, "Aligning learning goals with business objectives ensures that skill development translates into tangible business outcomes."

Personalized Learning Paths

Personalized learning paths are key to effective upskilling. Different roles require different competencies, and learning programs should be adapted to meet these specific needs. DataCamp's collaboration with Allianz illustrates the impact of personalized learning paths, with 22 different tracks for various technologies and functions. This approach not only enhances individual skills but also drives organizational efficiency and innovation. As Adele highlighted, "By personalizing learning paths, organizations can maximize the ROI of their upskilling efforts and empower employees to excel in their roles."

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