Our Vision on Analytics Outcomes

16 February 2024 | 2 minutes of reading time

At i-spark, we firmly believe that the use of data in business intelligence typically culminates in several data products. Each of these falls into one of three distinct categories. Each of these categories plays a distinct role in the handling and application of data, collectively playing a pivotal part in unlocking the true value of business intelligence embedded within the data.

The three data product categories

Ad-hoc Analysis Results: When tackling specific questions or hypotheses, we will perform the tailored data analysis to provide clear answers, focusing on actionable insights that reveal trends and unpack the reasons behind various patterns. Examples of analyses may include assessing a campaign's effectiveness, exploring factors contributing to customer churn, or pinpointing opportunities for expansion. The results are typically presented in a document format such as PowerPoint, which go beyond figures and visualizations to include explanations, summaries, and often recommendations. The “less is more” adagio really applies to this situation: instead of presenting an overload of visualizations, we curate and prepare only what is necessary to support the data analysis. Dashboards: For ongoing insights and metrics visualization, we model and structure data to support continuous visualization. This leads to the development of custom dashboards, crafted with tools like Looker, Looker studio, Klipfolio, Tableau, Power BI or custom-built solutions, offering real-time insights and decision-making support to stakeholders. Input for Activation Tools: In other instances, data encompasses not only visualization and descriptive analysis needs but it is also destined for application in activation tools, such as recommendation engines or marketing automation tools. To ensure the data is ready for these activation applications, it undergoes a preparation phase. This ensures that the data pipeline is finely tuned and fully compatible with these activation tools, enabling seamless integration and optimal performance. While these are just three categories, this doesn’t mean that there are just 3 deliverables. Depending on the use cases you could theoretically deliver 10 ad-hoc analysis reports, dashboards for 20 departments and 5 pipelines to activation tools for your business or client.

The End Goal: Data Utilization

The value of data truly manifests when it is aligned with the use case. Whatever use case is important for you, it’s useful to think of them in terms of one of these three categories. It may surprise you how often we are asked to create a dashboard in order to answer an ad hoc question or to create a table with customers that fall in some promising category without having thought at all about the definition of promising. Our forthcoming article, 'Unraveling the Distinct Worlds of Data Analysis and Data Visualization (Dashboarding),' will showcase the distinctions between the two most widely applied data analytics outcomes. These two articles, when combined, will serve as a guide to assist in selecting the right outcome that best suits your specific needs. As a final note, to avoid confusion. While in our opinion all data products fall in one category, this doesn’t mean that we at i-spark only deliver one of these types. At i-spark we also prepare analytics stacks or data platforms where we hand-over the semi-finished data products to our customers’ own data team for further processing. So in our projects the end result may be a data lake or data warehouse, but this should never be the end product of the data. After all, if the data is not used in a report, a dashboard or an activation tool, why use the data at all? Curious about the perfect analytics solutions for your business? Speak with our experts now for recommendations to optimize your data's potential.