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You’re collecting more data than ever before—but do you have the skills to collect and analyze that data efficiently? Give your teams the 21st-century skills they need to work with data in the real world. DataCamp for Business gives you the power to upskill everyone on your team to make better data-driven decisions—faster.
Digital Transformation in Finance: Upskilling for a Data-Driven Age
Over the past decade, big data and digital technologies have disrupted industries and consumer behavior alike. IDC and Statista estimate that the volume of data generated experienced a thirtyfold increase in the past ten years alone. None is more equipped to take advantage of this data deluge than the financial services industry. However, just as it is rife with opportunity, the financial services industry meets unique challenges when seeking a data-enabled digital transformation.
While compliance, data quality, and infrastructure are key challenges standing in the way of operationalizing data science at scale, no challenge is more pressing than the data fluency skills gap. In this white paper, we outline the unique challenges when upskilling for data fluency in finance, the highest impact data science use cases financial services organizations can start implementing today, and the skills needed to get them off the ground.
The future of work is data. As the amount of data in the world grows at an exponential pace, learning data science skills is increasingly important for professionals in all industries to make data-driven business decisions. To meet this need, learning professionals need to rapidly develop scalable, high-quality data science training programs and use data to measure the effectiveness of their training programs.
This webinar begins with a discussion about how data is changing the world. Adel Nehme from DataCamp will provide examples of how employees of all types are learning and utilizing data science skills to positively impact their businesses.
Next, Sheil Naik from Bloomberg will talk about how his team partnered with DataCamp to deliver a blended learning program focused on teaching data technologies to hundreds of employees in Bloomberg’s Global Data organization from around the world. Finally, Sheil will show how his team used the same analysis techniques taught in Bloomberg’s Data Analysis with Python program to analyze Python usage data to measure employees’ behavioral change at Bloomberg.
Train Your Workforce to Thrive in a Data-Driven Age
Data Roles for Data Transformation
In this webinar, we’ll introduce you to the concept of data roles—a new way to think about data transformation within your organization. We’ll discuss the benefits of using these personas to structure your data-focused learning and development programs and how to start mapping roles across your organization. Fill out the form for access to the webinar and slides.
The business world is overloaded with buzz terms like artificial intelligence, machine learning, AI transformation, deep learning, and data science. These fields, technologies, and tools are changing the competitive landscape across verticals and influencing business outcomes.
In this eBook, we draw the line between these loaded terms and offer practical guidance:
Distinguish where artificial intelligence, machine learning, and data science intersect and diverge
Avoid common pitfalls and follow best practices in machine learning
Craft your data strategy to include data both big and small
Find out how point-and-click tools can reduce your barrier to entry to data science and machine learning
Explore what it takes to build a data-driven culture