The Lone Wolf of Data: Challenges Faced by One-Person BI Teams

In today’s data-centric business landscape, the role of Business Intelligence (BI) is indispensable. BI empowers organizations to make data-driven decisions, uncover insights, and gain a competitive edge. While larger enterprises often boast robust BI teams, a significant number of organizations, especially startups and small businesses, rely on a lone individual to handle their BI needs. In fact, you may be the one-person BI Army at your own organization.

Here are some challenges that one-person BI teams face regularly:

1. Limited Resources

One of the most glaring challenges for a one-person BI team is limited resources. Unlike larger organizations, they may not have access to dedicated budget allocations, comprehensive training programs, or specialized tools and technologies. This constraint can hamper their ability to implement complex BI solutions. Limited time, budget and people can all have an impact on their ability to deliver. There may be multiple demands for data and reports, making it hard especially when data is scattered across different systems. It is also very possible that there is no data team that is able to assist with data centralization and gathering.

2. Time Constraints

Time is a precious commodity for a one-person BI team. Juggling data collection, transformation, analysis, and reporting, along with other organizational responsibilities, can be overwhelming. Meeting tight deadlines and addressing urgent data requests can be a constant struggle.

When you need to deliver on your requirements quickly, it can also significantly impact the quality of produced products. You can for example, see an impact on the quality of reporting is the majority of time was spent on data retrieval. This is where it becomes essential that time is not spent on things that can be easily automated.

3. Data Volume and Complexity

The sheer volume and complexity of data can be daunting for a single individual. Managing data from various sources, ensuring its quality, and performing in-depth analyses can be an uphill battle. Handling big data or large datasets becomes especially challenging without the support of a dedicated team.

4. Data Governance and Security

Maintaining data governance practices and ensuring data security is a multifaceted endeavour. A one-person BI team may find it challenging to establish and enforce data governance policies, maintain compliance with regulations, and respond effectively to data breaches or security incidents.

5. Technical Expertise

BI often requires a range of technical skills, from data extraction and transformation to database management and data visualization. A single individual may need to continually acquire and expand their technical knowledge to keep pace with evolving BI technologies and tools.

6. Isolation and Collaboration

Being the sole BI expert in an organization can lead to professional isolation. Collaborative problem-solving and brainstorming sessions that often occur within larger BI teams may be missing. This lack of diverse perspectives can limit the range of solutions and ideas.

There can also be a lack of data accessibility between departments or applications. These data silos can make it difficult to access required data, taking more time to deliver on requirements that have dependency on the isolated data.

7. Scalability

As organizations grow, so do their data needs. A one-person BI team may struggle to scale their operations to meet increasing demands for data analysis and reporting. This can result in bottlenecks and a slowdown in data-driven decision-making.

8. Burnout

The workload and pressure on a single BI professional can lead to burnout. Continuously managing data-related tasks without respite can affect job satisfaction and overall well-being.

9. Succession Planning

In the event that the sole BI expert leaves the organization, there may be a lack of succession planning in place, leaving the organization vulnerable in terms of data management and BI capabilities.

A solution to these challenges

There is no silver bullet that will solve all the issues faced by one-person teams, but there are tools that can significantly assist them in delivering their data and reports more efficiently, reliably and quickly. These tools include platforms allowing you to load and distribute data more efficiently, specifically low-code platforms.

The use of such a platform can:

• Lower time required to load data from multiple sources
• Simplify the building of ETL/ELTs or data pipelines
• Lower the skill requirement to do complex automation tasks
• Assist in the delivery of data via email, file extract or APIs that
• Lower time to develop these applications

For example, one such tool is Linx, a low-code back-end development platform that works well for integration. This naturally transfers to data integration, but you can do so much more than that. You can load any target into any source, combine data sources and even deliver your generated reports or notifications to any user via a multitude of channels. This is all facilitated by the low-code development interface that allows users to build their applications by dragging and dropping components.

For example:

• Load data from various sources (an Excel file, a CSV, your ERP/CRM system and more)
• Apply data validations and transformations
• Build data governance reports and send them out to the users
• Load that data into a data store (such as a database for data centralization)
• Make the data available to any system, user or application via file extracts or APIs that can be created in minutes
• Build throwaway processes to load data quickly
• Automate data loading from files, APIs or other data sources to execute once a month, daily or even yearly.

This works well for BI developers or analysts due to the low-code interface. They simply need to develop their application by using the drag-and-drop interface and then click the deploy button to have their application deployed and hosted on a Linx server. This means there is no need for complicated deployment pipelines or hosting strategies.

Here is how the right tool can solve the above-mentioned issues:

1. Limited Resources: Easier development in a quicker timeframe translates to lower costs and fewer people required to do the job.

2. Time Constraints: Quicker development of automation and applications.

3. Data Volume and Complexity: Simplified complex data import from various sources.

4. Data Governance and Security: Easier development and automation of data governance processes.

5. Technical Expertise: Lower technical requirements due to low-code or user-friendly interfaces.

6. Isolation and Collaboration: Accelerated development of data integration processes to remove data silos.

7. Scalability: Automating repetitive tasks, especially data loading and distribution.

8. Burnout: The easier creation of automated processes removes stress and pressure from people as those tedious tasks are off their plates.

9. Succession Planning: Low-code or platform tools are generally easier to understand and document because of their visual nature.

Conclusion

While one-person BI teams face numerous challenges, they play a vital role in organizations that may need more resources to establish larger BI departments. Overcoming these challenges often requires a combination of resourcefulness, continuous learning, and leveraging user-friendly BI tools. Using the right tool can make all the difference and empower a one-person BI team to meet their requirements on time.