LinkedIn and 3rd parties use essential and non-essential cookies to provide, secure, analyze and improve our Services, and to show you relevant ads (including professional and job ads) on and off LinkedIn. Learn more in our Cookie Policy.
Select Accept to consent or Reject to decline non-essential cookies for this use. You can update your choices at any time in your settings.
Sign in to view more content
Create your free account or sign in to continue your search
Thanks for letting us know! You'll no longer see this contribution
Incorporating external data sources into your BI strategy is like adding hot sauce to your favorite dish – it can really spice things up! 🌶️ But remember, it's not just about dumping all the data into the mix; it's about finding the right sources that complement and enhance your existing insights. Think of it as a master chef carefully selecting ingredients to create a culinary masterpiece. Bon Appétit to your data-driven decisions! 🍽️💡 #BIInsights #DataSpice
Thanks for letting us know! You'll no longer see this contribution
Integrating high-quality external data sources, performing comparative analysis, and applying advanced analytics. This approach enriched our data visualizations and provided a comprehensive view of market dynamics, while ensuring data security and compliance.
Thanks for letting us know! You'll no longer see this contribution
First, assess the needs for external sources of data in the model for instance integrating macroeconomic indicators like Inflation and FX rates and their impact on quarterly projections could be a reason. Add their data definitions and rationale to the data glossary/dictionary. Ensure the connection to the live API is secure and if not, we could use a different approach to batch the data in other interim tables. Ensure this data is structured in a way it can easily be integrated say in tabular format, imputation of missing values (forward and backfilling), and aligning dates and data types, etc. Perform key statistical tests like multicollinearity to reduce confidence interval deviation. Then you can apply them effectively in your models.
Thanks for letting us know! You'll no longer see this contribution
To effectively incorporate external data sources and elevate your BI insights, start by identifying sources that complement your internal data and align with your business objectives. Assess the quality, accuracy, and reliability of the external data to ensure it meets your standards. Integrate and cleanse this data using ETL processes to maintain consistency within your BI systems. Leverage the enriched data to create more comprehensive analyses, revealing trends, benchmarks, and insights that were previously inaccessible. Finally, continuously monitor the performance of these data sources to ensure ongoing relevance and accuracy in your insights.