10 Absolutely Critical Citizen Data Scientist Skills
Raza Sheikh
Author
Oct 12, 2022
Data & Analytics is a rapidly-growing field, and it's one of the most in-demand categories out there... And with good reason – data is becoming increasingly essential to businesses of all sizes in nearly every industry as they strive to make better, more informed decisions.
But what exactly are data & analytics? And what are the different roles within the field?
In this blog post, we will explore the many different facets of data & analytics and the various roles that make up this exciting and ever-evolving field. From data scientists to analysts to engineers, read on to learn more about the different positions in data & analytics and what each entails.
What exactly are data & analytics?
Data and analytics are two terms that are often used interchangeably, but they actually refer to two different things.
Data is the raw information that is collected, while analytics is the process of turning that data into insights. Let's keep it simple!
What are the different roles within the field?
There are a variety of different roles within the field of data and analytics, each with its own set of responsibilities.
Primarily let's brush on the data journey.
The data journey is the process of acquiring, storing, processing, and analyzing data.
This process can be divided into four main phases:
1. Data acquisition: This phase involves collecting data from various sources.
2. Data storage: This phase involves storing the collected data in a suitable format.
3. Data processing: This phase involves processing the stored data to extract useful information.
4. Data analysis: This phase involves analyzing the processed data to draw conclusions or make predictions.
The role of Analytics managers/BI manager/D&A manager oversees the work of data analysts and data scientists. They also develop strategies and set goals for the use of data and analytics within their organization.
A data architect is responsible for designing and managing data systems. They work with data engineers to develop efficient ways to store and access data. Data architects also work with business analysts to understand the needs of the business and how data can be used to support decision-making.
Data engineers are responsible for the construction and maintenance of data pipelines. In addition to their engineering duties, data engineers also work with data scientists to help them understand the data and develop models. Data engineers typically have a background in computer science or software engineering.
Data analysts play a vital role in helping organizations make sense of their data and glean insights that can improve decision-making. In many cases, data analysts are responsible for designing and conducting analysis on data sets, as well as communicating their findings to stakeholders. To be successful in this role, data analysts must have strong analytical and problem-solving skills, as well as experience working with various data analysis tools and techniques. They must also be able to effectively communicate their findings to non-technical audiences.
Data scientists are in high demand as organizations strive to make better use of their data. They need to be able to collect, clean, and analyze data and then use their findings to improve business operations. Data scientists typically have a strong background in math and statistics, and they are often comfortable working with large datasets. They also need to be able to effectively communicate their findings to non-technical audiences. If you’re interested in becoming a data scientist, you should consider pursuing a degree in data science or a related field. You can also find online courses and boot camps that will teach you the skills you need to succeed in this field.
Citizen Data Scientists to Maximize Your Data & Analytics Strategy
Data and analytics are critical for any organization that wants to stay competitive. But what if you don’t have the budget to hire a team of data scientists?
One solution is to develop a citizen data science program where employees from other departments are trained to become data analysts. This can help you maximize your Data & Analytics strategy without breaking the bank.
What is a citizen data scientist?
A citizen data scientist is a business user who has some data analytics skills and knowledge but is not a full-fledged data scientist. The term was coined by Gartner in 2012 and has been gaining popularity ever since.
There are several reasons why organizations would want to empower their business users with some data analytics skills.
First, it can help to close the so-called "analytics gap," which is the gap between the demand for data-driven insights and the availability of trained data scientists.
Second, citizen data scientists can help to democratize data analytics within an organization, making it more accessible and widespread.
And lastly, they can provide a cost-effective alternative to traditional data science roles, since they require less training and development time.
So how do you become a citizen data scientist?
There is no one-size-fits-all answer, but there are some key things you need to have to succeed in this role.
First, you need to have some technical skillset – you should be able to use at least one statistical software package and one programming language.
Second, you need to be comfortable working with large amounts of data.
And lastly, you need to have strong business acumen and domain knowledge to translate your findings into actionable insights for your organization.
What are the benefits of using citizen data scientists?
There are many benefits to using citizen data scientists within your organization. Perhaps the most obvious benefit is that they can help you maximize your data and analytics strategy. By leveraging the power of data, citizen data scientists can help you make better decisions, faster. They can also help you improve operational efficiencies and reduce costs.
In addition, citizen data scientists can help you tap into new markets and understand your customers better. They can also help you identify new business opportunities and areas for growth. Finally, citizen data scientists can help you build a more agile organization that is better equipped to respond to change.
How can you maximize your Data & Analytics strategy with citizen data scientists?
Citizen data scientists can help organizations to maximize their Data & Analytics strategy in a number of ways.
Firstly, they can help to identify opportunities for further data collection and analysis.
Secondly, they can provide insights and recommendations based on their analysis of organizational data.
Finally, they can help to develop and implement Data & Analytics strategy within the organization.
Organizations should therefore consider how they can make use of citizen data scientists within their organization to maximize their D&A strategy. One way of doing this is by establishing a dedicated team or department of citizen data scientists, who can work alongside other professionals within the organization, such as data analysts and business intelligence experts.
Alternatively, organizations could make use of external consulting firms that specialize in working with citizen data scientists. Whichever approach is taken, it is important that organizations ensure that their citizen data scientists are given access to the necessary resources and support to be effective.
Case studies of businesses using citizen data scientists
As organizations strive to become more data-driven, the role of the citizen data scientist is becoming increasingly important. Citizen data scientists are employees who are not trained in data science but have the ability to analyze data and solve business problems.
Organizations can benefit from citizen data scientists in a number of ways. For one, they can help to fill the gaps left by traditional data scientists. Traditional data scientists are in high demand and can be difficult to find and retain. Citizen data scientists can help to fill this gap by providing organizations with the ability to analyze data and solve business problems.
Another benefit of citizen data scientists is that they can provide insights that would otherwise be missed by traditional data scientists. Because they come from a variety of backgrounds, citizen data scientists often have different perspectives on problems than traditional data scientists. This diversity of perspective can lead to insights that would otherwise be missed.
Finally, citizen data scientists can help to improve organizational decision-making. When traditional data scientists are not available, organizations often have to make decisions without the benefit of data analysis. Citizen data scientists can provide the organization with the ability to analyze data and make better decisions.
One example of an organization that has benefited from citizen data scientists is Walmart. In 2015, Walmart launched a program called DataScience@Walmart to train employees in data science. The goal of the program was to empower employees to use data to solve business problems.
Since launching the program, Walmart has seen several benefits. For one, the company has been able to fill the gap left by traditional data scientists. In addition, Walmart has seen an increase in the number of insights generated by employees. Finally, Walmart has seen improved decision-making as a result of the program.
Conclusion
There's no doubt that data science is a hot topic in the business world today. But what exactly is data science, and how can it be used to maximum effect in your company? This is where citizen data scientists come in. Citizen data scientists are employees who have the necessary skills to analyze data and draw insights from it, but who don't necessarily have a formal background in data science. Utilizing citizen data scientists within your organization can help you get the most out of your data and make better decisions for your business.