Business intelligence (BI) professionals use various tools to create data-driven solutions, such as data models, pipelines, visualizations, and dashboards. These solutions can provide valuable insights and help organizations make better decisions. But to do that effectively, they need to have data availability. Data availability refers to the degree or extent to which timely and relevant information is readily accessible and able to be put to use.
However, there are many factors that can affect data availability and compromise the quality of BI solutions. In this post, we will discuss some of these challenges and how to overcome them.
What are the Data Availability Challenges?
Some of the most common data availability challenges are:
• Integrity
• Visibility
• Update frequency
• Change
Let's look at each challenge in more detail.
Integrity
Data integrity involves the accuracy, completeness, consistency, and trustworthiness of data throughout its entire life cycle. Typical issues related to data integrity include duplicates, missing values, inconsistent formats, or not following business rules. These issues can lead to inaccurate or incomplete results and damage the credibility of BI solutions.
To ensure data integrity, BI professionals need to perform data quality checks, such as validating, cleaning, standardizing, deduplicating, and enriching data. They also need to document the data sources, processes, and rules that they use for their analysis.
Visibility
Data visibility is the degree or extent to which information can be identified, monitored, and integrated from disparate internal and external sources. For example, employees working in a company's marketing department might not know what data is stored in the finance department. Or someone working in the customer service unit might have data files that contain useful information, but no one else is aware of them.
On the other hand, when there is clear data visibility, it is possible to achieve accurate and timely insights and improve the organization's responsiveness and agility. To achieve this goal, BI professionals need to work with their colleagues to create a list of data repositories for stakeholders. They can request a short interview with the data owners or ask them to complete a quick online survey about the data they collect and use. This is a simple but effective exercise to discover the kind of data that is available.
Also, keep in mind that data visibility challenges do not only exist within an organization. Sometimes BI professionals are unaware of useful external data. As you may know, there are many free public datasets, such as government statistics, social media trends, industry reports, and more. All of these can contribute to a successful BI project.
Update Frequency
Often times, BI projects will involve multiple data sources. It is very common for different sources to refresh at different times, such as daily versus weekly. For example, a BI professional works for a clothing retailer based in France and analyzes product sales volume by region. If a supplier changes its prices in the middle of August, all of that month's sales would reflect the old prices simply because the supplier's data has not been updated yet in the BI system. Either the supplier's data needs to refresh sooner to match sales data or the retailer should look at all data on a weekly basis.
This is why it is important for BI professionals to understand how the update frequency of different data sources can affect insights. Even if individual data sources are perfect, the integration aspect can be challenging.
Change
Change is inevitable in almost every aspect of our lives and data is no different. Data availability may be affected by a change in internal procedures such as a system upgrade or a new record-keeping process. It may also change externally because of a user interface change or an adjustment to a particular algorithm.
To address this issue, BI professionals need to have a plan for how they will keep stakeholders up-to-date on changes that might affect the project. They should encourage team members to think about what tools or methods they are using now, what could change, and how it may influence the data being tracked and how to fill any potential gaps.
Why Data Availability Matters in BI?
Data availability matters in BI because it helps you:
• Confirm that you are using the right data for the right stakeholders
• Ensure that your data is in the correct format and can be effectively used and shared
• Make sense of your results and explain them clearly
• Enhance your understanding and decision-making
• Achieve better business outcomes
By addressing data availability challenges, you can create more reliable and impactful BI solutions that deliver value for your organization.
