Data engineering to unlock the potential of BI
Business intelligence (BI) supports organizations to extract valuable insights from their unstructured and structured data to facilitate strategic decisions. However, unlocking this potential requires complex data to be managed through data engineering, including data ingestion, storage and processing, before it can be transformed into tangible values.
BI to enable fact-based business decisions
BI sits at the forefront amongst modern business leaders as it unlocks a visual understanding of complex data and facilitates informed strategic decisions. The insights presented in intuitive visualizations enable executives to proactively align strategies with dynamic market conditions, anticipate trends, enhance operational efficiency, and thereby drive long-term success.
“What is often forgotten though is how long
the path to an intuitive dashboard is”
Most companies own vast amounts of data collected through multiple sources. What is often forgotten though is the long path to a dashboard. The data must be carefully engineered through multiple steps to ensure that the potential of BI can be absorbed.
Data engineering - From data to dashboard
To facilitate impactful data-driven decision-making through data visualization, organizations need a well-defined data engineering strategy for defining and developing the following key steps:
•Data ingestion: Develop data pipelines to seamlessly ingest raw data from various sources such as databases, logs, or social media platforms into your data storage solution
•Storage solution: Select a robust and appropriate data storage solution such as a data lake or warehouse, for efficient and organized data management. Consider leveraging cloud-based services like AWS, Azure and Google Cloud for scalability and accessibility or develop an on-premises solution aligned to specific organizational needs
•Data processing: To enable the creation of visualizations, process unstructured data into highly refined and aggregated data and store in business-level tables using e.g. AWS Glue
Executing the key steps in the data engineering process enables processed data to be presented in a visually comprehensible manner using for instance Power BI or Tableau, aiding decision-makers in extracting actionable insights from the data.
Data engineering – A core capability!
As the amount of data continues to grow the importance of data-driven decisions for organizations is evident. Consequently, data engineering is foreseen to become a core capability for organizations to effectively manage complex data and extract valuable insights through visualizations