Hal Ronald Varian, the chief economist at Google, said, "Between the dawn of civilization and 2003, we only created five exabytes; now we're creating that amount every two days. By 2020, that figure is predicted to sit at 53 zettabytes (53 trillion gigabytes) — an increase of 50 times."
This might be why 'The Economist,' in 2017, stated that "The world's most valuable resource is no longer oil, but data."
Over the past few years, businesses of all sizes are in a mad rush to mine and refine the 'new oil' called data, which is proliferating the digital space like never. The massive data boom has dramatically transformed the way people do business, and companies are constantly trying to figure out innovative ways to use the Big Data explosion to their advantage.
Though the influx of data is difficult to decipher and digest, enterprises realize that 'mining and refining' it is increasingly becoming crucial, as it can provide them with actionable insights that translate into accurate decision making.
In today's business scenario, organizations understand the relevance of Big Data, and that is pushing the demand up for data miners and data scientists, who can implement business intelligence technologies to convert raw data into meaningful information.
In their pursuit to gain smart, actionable intelligence, forward-thinking businesses are putting a great emphasis on data science and data analytics to speed up their operations, reduce business costs, and to design personalized services for customers.
To maintain AI-tech agility, leading global companies like Spotify, Salesforce, Netflix, and Google are investing heavily in data science and cloud data analytics. These data-driven enterprises are demonstrating their heightened interest in the field of data science and data analytics through high-value acquisitions in recent times. While Google acquired a business intelligence startup, Looker, for $2.6 billion, Salesforce took over data science company, Tableau, for $1.57 billion, to facilitate the creation of end-to-end analytics solutions.
With regard to job openings for data scientists, LinkedIn reveals an increase of 56% in the US since 2018. According to an employment-related search engine, Indeed.com, there has been a rise of 344% since 2013, with a 29% year-over-year escalation. Despite the strong demand, there is a big talent gap to fill positions in emerging data science and data analytics job roles, involving Machine Learning, Artificial Intelligence (AI), or Robotics.
To fill the gap, enterprises, across the globe, are relying on corporate training programs that focus on upskilling employees, which, many business leaders feel, is the most cost-effective, fastest, and smartest solution to address the talent crisis.
Upskilling the existing workforce through continuous employee training is not only helping companies to improve retention, but it is also providing IT professionals, an opportunity to heighten their knowledge while remaining employable.
What is Upskilling?
Upskilling is a process adopted by employers to teach their employees new skills that make businesses and professionals more competitive. Besides creating a holistic workplace culture that promotes engagement, wellbeing, opportunities, success, and leadership, upskilling also impacts the company's bottom line directly — major benefits of upskilling for both employees and employers.
Trained professionals leaving a company can be catastrophic in terms of recruiting expenses and lost productivity, which can go up to a few thousand dollars. By offering to upskill via corporate training, organizations augment value addition while sending a message to employees that they are special and that the company cares for them. The increased engagement improves retention.
Several studies reveal that organizations that conduct regular employee training and development programs have a happy, satisfied workforce. Upskilling helps employees see their career advancement, which boosts their morale and generates a more in-depth perception of their purpose in the company.
Pulls New Talent
An upskilled workforce, contented with an organization, are the best brand ambassadors and advocates for the company. Most likely, they will post positive feedback on social media networks, and they will also recommend the organization to their circle of friends and family.
Reduces Waste of Time
These days, with the stigma of changing jobs disappearing, many employees believe that they should go job-hopping every 2 to 3 years to ensure continuous learning. However, if employers provide their employees with ample opportunities for learning, the workforce can spend their time focusing on performance and productivity, without wasting time applying for new jobs.
Helps Gain a New Skillset
Upskilling enables the workforce to profit from gaining knowledge in new areas, which can lead to the discovery of new passions, talent, and, ultimately, brighter career options. No one can predict the future, so the discovery of new talents can serve as an eye-opener for tomorrow.
The Blended-Learning Approach Is the Most Efficient and Cost-effective Solution for Data Science and Data Analytics Upskilling
The blended-learning approach is a mixed-method, interactive education module in which a student learns via live, online classroom training, customary face-to-face teachings, and through on-demand videos. This unique approach offers flexibility, which enables busy professionals to upskill according to their convenience. Here are a few reasons that make blended-learning the future of higher education.
Easy and Systematic Learning
Incorporating classroom workshops, multimedia presentations, and gamification to motivate participation, the systematic blended learning approach offers a rich, repeatable, and engaging educational experience that makes learning fun and easy. Usual classroom sessions cannot deliver this type of interactive training.
Blended-learning approach includes a range of assessment modules, such as projects in real-time, quizzes, and tests, which enable organizations to assess employee retention levels easily. This allows employers to address and clear doubts to improve retention.
The blended-learning model needs minimum infrastructure. There are no travel expenses or costs to develop training material, which makes this learning process affordable for any company aiming to upskill employees.
Instructor-led, live classroom sessions make blended-learning accessible to teams and managers based around the world. Communications via online communities and forums ensure better connectivity between teachers and learners.
Summing It Up
Successful companies, at their core, have employee training, which produces a skilled workforce that adds significant value to the business with a low exit rate. Upskilling is key to keeping the workforce — especially the top pros, for instance, data science and data analytics professionals — and blended-learning is the solution.
The blended-learning module represents a paradigm shift in the way knowledge is delivered and shared. It can optimize employee skills and offer better control and flexibility to learners while giving employers opportunities to cut costs and improve ROI.
However, to get the best out of blended learning to upskill employees for emerging technologies, companies must rely on a trusted platform like Simplilearn. They have the required experience and expertise to handle world-class blended learning programs.
Leveraging mixed learning styles, Simplilearn's custom-built blended-learning courses deliver results-driven, high-engagement training at scale, across geographies, while offering students complete control over the time, place, and pace of learning. To speed-up careers with the Data Scientist Course — covering key technologies like Spark, Hadoop, Tableau, Python, SAS, and R — contact Simplilearn today.