Presented by Skillsoft


Humans create trillions of megabytes of data per day, and this data is not trivial. In fact, for most organizations, it’s ‘need-to-know’ information about the routines, habits, likes, and dislikes of their employees and customers. This data takes the form of customer records, chat logs, in-house data collection, tracking data, emails, SMS messages, and more.

Having surplus information is excellent, but much of the data is unstructured — meaning the only way to extract value from it is by having personnel and tools in place within your organization that can do so. However, only once that data is organized and analyzed can it provide operational benefits for an organization.

Learn how the U.S. Department of Health and Human Service (HHS) and Abt Associates used training to drive impact with Data Science and Python.

A modern business cannot afford to operate blind, especially not now in the age of customer empowerment. Customers are armed with information about your business and your competitors’ business, and they have 24/7 access to your customer support. As a result, they are ready to hold your organization accountable or find a service that better suits their needs. Understanding how employees and customers interact with your organization is table stakes.

It’s very likely that you already have all the data you need to begin a digital transformation. In this article, we’ll explore several training solutions you can employ to upskill or reskill talent, or if you’re looking for new hires, this list can show you what skills you’ll need in order to focus your hiring efforts.

Because the data has a story to tell, putting people in place that understand how to tell that story and adopting tools that automate data cleaning and analysis should be your top priority. To illustrate the importance of these skills in the marketplace, we looked at learning trends and dug into our analytics. Skillsoft serves training to 70% of the Fortune 1000, including some of the top consulting companies partnering with organizations to lead data transformation. Here are the insights we derived from our course consumption metrics.

Courses with the most badges (course completions) earned:

  1. Software Data Analysis: Project Management Metrics
  2. Introduction to Artificial Intelligence
  3. Data Science Overview
  4. SQL Concepts & Queries
  5. Machine Learning
  6. Artificial Intelligence: Basic AI Theory
  7. Automation Design & Robotics
  8. Applying Predictive Analytics
  9. Data Access & Governance Policies: Data Access Governance
  10. Machine & Deep Learning Algorithms: Introduction

Badges earned February 1st 2021 — June 24th 2021 across all Skillsoft learners

This illustrates that users are highly motivated to understand the basics of data literacy — including the concepts behind operationalizing artificial intelligence and machine learning. Essentially, these users are training in the operational aspects of putting data into use. Users only earn a badge once they’ve gone through the course, have been tested on their skills, and pass at a high level. Simply put, when a user earns a badge, it means they have not only completed our course, but they’ve built durable skills as a result.

This list should also give you some ideas about where to start digital transformations within your organization. These are the courses users are taking and excelling at, and as a result, there are now more highly skilled people working in these disciplines. The key is to make sure they’re either working within your organization or that your employees are just as highly qualified.

Learners love data science

We also looked at which Skillsoft courses racked up the most consumption hours. Here’s what we found:

  1. Business Reporting: Getting Started with Power BI Desktop for Data Analysis
  2. SQL Concepts and Queries
  3. Power BI Desktop Bootcamp: Session 1 Replay
  4. Software Data Analysis: Project Management Metrics
  5. Business Reporting: Visualizing & Merging Data in Power BI

Again, we see a concerted effort by users to understand how to get the most out of data. With that in mind, we looked at courses with the most likes to give us an idea about what courses users enjoy.

Most liked courses:

  1. Power BI: Getting Started with Data Analytics
  2. Introduction to Artificial Intelligence
  3. Data Science Overview
  4. SQL Concepts & Queries
  5. Power BI: Data Modeling & Visualization
  6. Relational Database Concepts
  7. Software Data Analysis: Project Management Metrics
  8. Power BI: Data Preparation
  9. Big Data Essentials
  10. Power BI: Data Sourcing

As we can see from this list, it’s the analysis, data preparation, and visualization courses making people the happiest. These courses provide best practices for analyzing and sharing data to help users understand how to derive actionable insights from their data and transfer that data-backed insight to benefit the rest of the organization.

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With this data journey mapped out, we decided to see which industries are majorly focusing on data consumption, and what we found is exactly what we thought we’d find. The industries are hospitality, insurance, pharmaceuticals, banking and finance – all businesses primarily focused on serving others and delivering a good customer experience.

What learners want illustrates the gap in the marketplace

We decided to see if there were insights to be found in the top 10 user journeys taken by our users to round out this information. We found the top journey is Python Novice to Pythonista, #4 is Data Analyst to Data Scientist, and #10 is ML Programmer to ML Architect.

Users spend a lot of time learning Python, understanding data analysis at a high level, and gaining competency in machine learning. These are all necessary for data science projects — for those who don’t know, Python is the #1 language to use for data science projects, and Python is the most searched for topic in Skillsoft’s Tech & Dev course selection. Now, if we search up a level and look for what registered learners are looking for, we find that they are most interested in finding topics that deal with data tools and frameworks.

When we look at Skillsoft’s data on what our learners are searching for across all our data and technology courses, we find that 17% are solely focused on data. Most of those users are kicking off their data journey by learning about tools and frameworks. Others seek to understand the core concepts behind data science and how to operationalize data best.

Get ahead and stay there

The past few years of disruption and instability have ushered many organizations into digital transformations. A vital aspect of that transformation is ensuring that talent, from the top down, has a shared understanding of data science literacy.

Data literacy is not about a single tool, tools can easily create siloed workflows, and a new and better tool will always be along as soon as your talent masters the previous. The best way to successfully achieve data literacy is by holistically reskilling and upskilling your talent. Start with your data teams, then scale to the rest of the organization.

Reskilling comes into play when you have a group out of touch with the cutting-edge knowledge your organization needs to stay ahead of the trends. Technology develops so quickly that this is a prevalent group in pretty much every organization today. Part of this journey must include opportunities to practice what is being taught. This group understands the value of building durable skills through doing. Having prescriptive, but not overly rigid content created around your learners’ roles is an essential ingredient for this segment of your population. People are the most valuable resource a company has, and efforts to reskill employees instead of hiring new will undoubtedly save time and money.

This is not to say that hiring new is a bad thing. We’ve found another effective tactic is to upskill a potential group of candidates. Many organizations choose to employ generalized talent from colleges and academic institutions and give them the training and knowledge they need to succeed. This cohort likely needs the prescriptive part of a role-based curriculum the most. They have minimal expectations of what to learn next, so guidance and feedback are necessary. Like the prior experience group, this group also needs plenty of room to practice what will become their durable skills.

Once data is in play, you’ll be able to run analytics, create visualizations, find insights, and tell the stories living in your data.

To start putting a plan into action, you can contact the Skillsoft sales team and build a learning culture with enterprise-spanning impact.

Mike Hendrickson is Vice President ofTechnology and Developer products at Skillsoft. Prior to Skillsoft, Mike spent 15 years at O’Reilly Media, Inc., where he most recently was the VP of content strategy. Mike is a technology strategist with extensive experience establishing, building, and maximizing relationships with industry leaders, companies, and partners.


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