Organizations across the world are striving to be data-driven and use data more effectively to inform decision-making at every level of the business. However, according to the 2021 Big Data and AI Executive Survey from NewVantage Partners, only 40% of companies today manage their data as if it were a business asset. In other words, ambition is outpacing reality by a wide margin.

One of the biggest obstacles to closing the gap is the current IT talent shortage. Enterprises are especially struggling to find capable data science and data engineering resources. There are roughly 500,000 jobs open for data engineers right now, and yet, only 50,000 graduates with the right skills enter the workforce every year. Compounding the IT skills gap problem is the ongoing Great Resignation movement brought about by the COVID-19 pandemic. Millions of people have left the workforce over the past two years without any intention of returning to their jobs, leaving younger professionals with big shoes to fill.

Given these trends, it’s only becoming harder for organizations to evolve into data-driven enterprises. Leaders today know where they want to go, but many don’t have the people, processes, or tools necessary to accomplish their objectives. Fortunately, through automation and data democratization, there is a viable path to building a data-driven business in 2022. 

Organizations can empower their existing IT professionals with new technologies that accelerate data-oriented workflows. They can also make data more accessible and approachable to users throughout the enterprise, thus extending data’s value and reach significantly. With these changes, executives can maximize IT productivity and mitigate some of the biggest risks facing organizations from becoming data-driven. 

Leveraging Automation to Streamline Data Operations

Many companies today fail to use their IT resources to their full potential, especially when it comes to data management. Tech professionals are often bogged down in manual activities, such as data preparation and data transformation. According to a recent survey from my company, IT talent is wasted on data prep, with respondents spending almost as much time prepping data (6.6 hours per week) as they do analyzing it (7.2 hours per week).

While countless organizations have made major strides in being able to gather, process, analyze, and use data, there is an opportunity for growth, particularly through automation. Too many skilled and valuable IT professionals are tasked with work that can easily be automated with new-age technology. By replacing manual tasks with automated workflows, leaders can free up IT capacity for more important data initiatives.

Automation can handle data preparation, data transformation, and data movement between systems. Data Governance and regulatory compliance can also be automated. Enterprises can leverage cloud object storage environments that have pre-defined security and robust governance policies, so IT professionals don’t have to spend time maintaining such infrastructure. The key lies in finding tools and technologies that can come alongside human workers and augment their skills without creating additional complexity. 

Another critical factor to implementing automation successfully lies in an organization’s ability to democratize internal data for widespread use. Without data democratization, it’s difficult to achieve a truly data-driven culture.

Democratizing Data Beyond IT

For most modern organizations, data volume is not a barrier to data-driven operations. Companies today have the information they need but cannot process what they have in a meaningful way. This is where data democratization comes in.

Data democratization refers to simplifying how all people, including technical and non-technical users, access and analyze data. The goal of democratizing data is to equip more individuals with rich insights that they can use to make better decisions in their day-to-day responsibilities. Data democratization is distinct from data literacy, which refers to how well people understand the data they have at their disposal. 

At a time when IT resources are scarce, leaders must think about how they can develop data science and data engineering skills internally. Doing so is challenging if data is inaccessible or unapproachable to most people in the business. Rather than treat data as an IT resource, leaders have to focus on cultivating a population of citizen data scientists (i.e., everyday business users) who can create value from data without needing advanced technical skills. 

In many cases, this will require companies to offer education and professional development opportunities to upskill existing employees. By closing the data literacy gap, enterprises can mitigate some of their exposure to talent shortages in the marketplace. Additionally, leaders should invest in modern data architectures, like data lakes and cloud-native data warehouses, that facilitate deeper and wider access to data. These technologies are crucial for distributed workforces that need to collaborate in real time.

Ultimately, data democratization and data literacy are about realizing the potential for all business professionals to leverage data for the benefit of the larger group. Executives who can extend data beyond IT will not only reduce the burden on their IT teams, but also accelerate data-driven transformation and decision-making across the organization. 

Focus Internally First in 2022

Leaders can’t rely on being able to recruit the data science skills they need to continue innovating and creating value. Instead, they have to expedite data workflows by automating data movement, migration, and transformation. On top of that, they have to level up current employees so that they can tackle higher-value projects without draining IT resources. By investing in new tools and processes that eliminate time-intensive tasks bogging down IT teams, data analysis can be opened to the entire organization, and executives can overcome current market challenges to become more data-driven in 2022.