How can you improve your team's performance in BI?

Once goals and roles are defined, it's helpful to capture them in writing and store the document somewhere accessible. Having this information in a written format ensures that everyone shares a common reference point. It also serves as a foundation for future discussions and adjustments as the needs and dynamics of the team or client relationships evolve.

Improving your team's performance in Business Intelligence (BI) involves a combination of strategic planning, skill development, effective collaboration, and the use of advanced tools. Here are several strategies to enhance your team's performance in the field of BI: Define Clear Objectives: Invest in Training and Skill Development: Promote a Data-Driven Culture: Collaborate Across Departments: Ensure Data Quality and Consistency: Select and Implement Suitable BI Tools: Streamline Data Integration: Encourage User-Friendly Dashboards: Establish Key Performance Indicators (KPIs): Implement Agile Methodologies: Promote Continuous Improvement: Provide Adequate Resources:

In a BI project, it's crucial to keep in mind that various stakeholders have distinct goals. The analyst building the report is focused on goals related to the data pipeline and report setup, whereas the business person seeking answers has a different set of objectives. Make sure to clearly outline and communicate the specific goals driving the creation of insights, as well as how these insights should be utilized. This way, everyone involved is on the same page about the intended outcomes and purposes of the project.

One of the key tools to help with data governance and standards is to have a clear certification process with full transparency on who is involved in certifying the data models and having clear documentation of the data model semantics. This certification lable should be clearly stated to all the upstream and dowstream users of the analytics application. Having a certification process promotes ownership and focus on driving governance standards.

Following the selection of an appropriate BI tool, it's crucial to focus on documenting data lineage as part of establishing data governance and standards. Data lineage refers to the life cycle of data, tracing its origins, movements, and characteristics throughout its journey in the system. Documenting data lineage is vital for maintaining the quality, security, and consistency of data. It allows your team to track the source of data, understand its transformations, and verify its accuracy and integrity.

To enhance the BI team's performance based on my experience, it's crucial to establish clear data definitions, create a comprehensive dictionary, articulate internal data policies, and ensure all team members are aware of business project requirements. These elements are essential for fostering consistency, improving efficiency, and boosting BI performance beyond data governance and standards.

From what I've learned, diving into data governance and standards right from the beginning can actually slow down the whole value creation process. For teams just starting their BI journey, the key is to kick things off, generate some insights, and not get too bogged down by perfecting data governance and standards upfront. This is especially important when you need to show value to get to invest further. Once you've got the hang of it and maybe stumbled a few times, that's when you know what tweaks are needed.

Here are two BI presentation tools to consider: #1 Tableau: Tableau allows users to create interactive and shareable dashboards. The platform is known for its user-friendly interface with drag-and-drop functionalities. However, the more advanced features require some learning, and Tableau can be expensive depending on your organization's size. #2 Microsoft Power BI: Power BI offers a diverse set of BI capabilities, including extensive data visualization, warehousing, and preparation tools. While it's powerful and scalable, the complexity of some of its features might pose a learning curve, and the most advanced capabilities are behind a subscription model.

Don't tie yourself too tightly to a single tool or supplier. Aim to keep your data storage and analytics tools loosely coupled. The analytics tooling field is evolving rapidly, and people have their own preferences. Maintaining flexibility on the analytics layer allows you to adapt and mix different tools based on what works best for your team and goals.

Experience a noticeable improvement by attempting this: Encourage Shadow Playing and Skill Showcases: Provide opportunities for team members to “shadow play” or take the lead in certain projects or tasks regardless of their usual role. This encourages individuals to showcase their potential and grow their skill sets, fostering a culture of empowerment and skill development within the team.

Set aside specific times during work hours for learning and development activities. This could be a regular slot each week or month where team members are encouraged to engage with learning resources or attend training sessions. Promote a culture that values continuous learning and improvement, where taking time to learn is seen as beneficial and necessary rather than a distraction from "real work". Recognize and reward learning achievements to further encourage this culture.

In technical fields such as business intelligence (BI), my experience suggests that job shadowing is a valuable method for knowledge sharing. This is because team members often possess comprehensive knowledge and can help identify any gaps or blind spots in specific details. Through efficient job shadowing, you can quickly reach the core aspects of the subject matter.

As BI is a dynamic and evolving field that requires constant updating of skills, knowledge, and best practices, I found shadow playing and focused training programs very beneficial for the team to keep themselves updated.

Como Gestor Financeiro prezo muito pela proximidade da área financeira com a área de BI e demais. Com essa sinergia o output se torna mais preciso e com vínculo ao negócio. Assim temos os dados transformados em dados para tomada de decis?es.

The ultimate win for any BI project is real, tangible business impact – and that's something to celebrate! Yet, in bigger organisations, the BI team might be a bit removed from the direct business impact. Closing this gap might take some effort in communicating the value across the organisation. If this doesn't happen, analysts can look for reports that are regularly used are likely delivering value to someone in the organisation. Identify the power users of these reports and ask them how the insights are benefiting them. In other words, using BI to improve BI.