Build a BI stack to monitor product performance

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BI stack Product Performance
Architecting a Robust BI Stack: Monitoring Your Product’s Performance Made Simple

In today’s digital-centric landscape, tracking product performance is crucial for businesses. It aids in understanding user behavior, identifying potential bottlenecks, and making data-driven decisions. But how do you capture all this data and make sense of it? Enter the realm of Business Intelligence (BI). This article explores how to build a BI stack for monitoring product performance effectively.

Laying the Foundation

Firstly, it’s crucial to understand that a BI stack isn’t a single tool, but rather a combination of different software components working together. The process begins by identifying the core components of your BI stack. Typically, this includes data sources, data storage (lakehouse), ETL tools (Extract, Transform, Load), and data visualization tools.

Identify Your Data Sources

The data sources constitute the raw materials of your BI stack. They can range from applicative databases and CRMs to APIs and cloud services. Large companies generate a lot of data (HR, marketplace, marketing, information system, website, etc), the key is to map the data sources in order to ensure that thechosen ones are relevant to the product’s performance metrics you want to monitor.

Choose the right data storage platform

Following this, the data warehouse is where the gathered data is stored and organized. It’s essentially the backbone of your BI stack. Cloud-based solutions like Amazon Redshift, Google BigQuery, or Snowflake are often the go-to choices due to their scalability and ease of use.

Leverage ETL Tools

Once you’ve identified your data sources and set up your data warehouse, the next step is data transformation. ETL tools help you extract data from various sources, transform it into a usable format, and load it into your data warehouse. Talend, Stitch, and Fivetran are just a few examples of powerful ETL tools.

Invest in Data Visualization Tools

Lastly, data visualization tools enable you to translate your data into understandable and actionable insights. Tools like Tableau, Power BI, and Looker allow you to create dashboards and reports that present your product’s performance in a visually compelling and interactive manner.

In conclusion, building a BI stack is like constructing a well-oiled machine. Each component has a specific role, and when they work in harmony, they empower you to monitor your product’s performance effectively and make informed decisions. However, it’s important to remember that the journey doesn’t end once the BI stack is in place. Regular maintenance and adjustments are required to ensure that your BI stack remains effective and continues to deliver valuable insights.

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Written by Alexandre B.

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