Blockchain Analytics and Data Pipelines
Development: Building and hosting the analytics stack to analyze network adoption and smart contract activity.
To track the growth and adoption of ICON, metrics need to be extracted, transformed, and loaded into performant databases for analysis. When the process is built right, insights can be gained in near real time to track items such as monthly active wallets or number of transactions for individual smart contracts and DApps over time. By analyzing the blockchain's adoption, the community can gain insights into user behavior and act on them by directing resources more appropriately to increase transactions.
This proposal focuses on building a robust business analytics tool suite to support blockchain analytics. It will use the same architecture being used on the top blockchains per the blockchain-etl github organization by orchestrating data pipelines with Apache Airflow and inserting the data into various relational databases for further analysis. The project will then build dashboards with Apache Superset for analysis with a long term support for additional metrics requested by the community. These visualizations can then be embedded into various block explorers or used by individuals doing exploratory analysis.
10 weeks
Initially the project will focus on high grading metrics for investigation and standing up infrastructure necessary for analysis. These two processes will be done in parallel and will take about two weeks complete. Next we will construct data pipelines, base tables, and query optimized tables. These databases will then be connected to a business intelligence dashboarding system to aid in exploratory analysis. After putting the process in production, we will package it up so that Insight data engineering fellows and members of the community can build additional metrics and visualizations.
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