When dealing with extensive data sets gathered from diverse sources, the task can sometimes pose challenges. To ensure your work stands out and maintains a competitive edge in your field, consider the following essential best practices in the data industry.
- Data Accuracy
When working with data, one of the most significant hurdles is ensuring data accuracy. Before delving into addressing the underlying issue, it is crucial to assess the accuracy of your data output. In SQL, there exist several methods to verify data accuracy, such as employing aggregate functions, applying relevant filters and conditions to roughly estimate the expected data. However, it's important to note that inaccurate input data will inevitably lead to imprecise end results.
- Handling Duplicate values
There are various SQL joins available, and if incorrect joins are created, there is a possibility that your derived database will contain manipulated data. Duplicate rows within your database can result in inaccurate outcomes.
To address duplicate entries in your data, SQL offers several methods, including utilizing functions such as Row_number(), count(), and Group by.
- Test your data
After constructing the dataset, it is considered a best practice to validate the results using real-life scenarios. This approach ensures that the derived data yields accurate outcomes, establishing confidence in utilizing this dataset for future projects.
Adopt the habit of testing your results by selecting a sample of data from the dataset. Ensure that the sample encompasses various date classes, as this will help identify any anomalies present in the dataset.
- Handling Anomaly
It is common to encounter anomalies in every dataset, which can lead to extreme outcomes that may not reflect real-world data accurately.
To address these anomalies in your data, it is essential to carefully examine the dataset and anticipate potential issues. Building expectations around potential data discrepancies is crucial. In SQL, there exist multiple methods to tackle this challenge, and it is advisable to continuously monitor and stay updated on these techniques as part of best practices.
- Visualization tools
In order to effectively convey data to a wide audience or leadership, it is essential for a business analyst to utilize visualization tools such as Looker, Power BI, and Tableau. Presenting data visually through appealing graphs and charts simplifies the storytelling process and provides a clear understanding to the listeners.
There are numerous types of charts and graphs available to suit various data requirements. It is important to familiarize yourself with the best practices and approaches for presenting your dataset in a compelling manner.
- Effective communication
Efficient communication plays a crucial role in assisting business analysts in comprehending stakeholder requirements, accurately gathering necessary information, and establishing a shared understanding among all involved parties. By engaging in clear and concise communication, analysts can effectively convey intricate technical concepts in a manner that is easily understandable to non-technical stakeholders. This fosters collaboration and ensures that business objectives and technical solutions remain aligned.
- Understand and solve the need
As a business analyst, it is essential to approach issues from a business perspective and offer appropriate and effective solutions. Your role extends beyond data collection and result delivery; a significant portion of your time will be dedicated to understanding requirements, engaging with stakeholders, and connecting the dots within the problem. This holistic approach allows you to uncover hidden solutions and provide valuable insights to address the challenges at hand.