Data Reliability Automated Liang-Bin Hsueh (hlb), Cofounder and COO of InfuseAI PipeRider https://www.piperider.io/

About Me • Cofounder of InfuseAI • ❤ Open Source • Reach me • Twitter: hlb • Facebook: iamhlb • LinkedIn: iamhlb

About InfuseAI Data Reliability Automated Streamline MLOps Our Products trusted by research institutes and leaders in sectors including FSI, manufacturing, and healthcare projects our product 
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Unity Software Inc. (NASDAQ:U) Q1 2022 Earnings Call Transcript “We lost the value of a portion of our data, training data due in part to us ingesting bad data from a large customer. We estimate the impact to our business of approximately $110 million in 2022 …”

Data Reliability • data is complete and accurate, and it is a crucial foundation for building data trust across the organization • Types of Data • Operational Data: data produced operationally. customer impressions, transaction records, … • Analytical data: data used analytically. Marketing churn, clickthrough rates, impressions by global region, … • Operational data runs your business; Analytical data manages your business

Fighting with Bad Data • Duplicate records • Incomplete fi elds like missing values • Inaccurate data entries like “InfuseAI”, “Infuse AI”, ”InfuseBI”, “Infuse CI” • Incompatible software migration like from one database to another • Schema or semantic changes

Data Analysis in Reality :(

Data Pipeline Thank to Karen Hsieh [Link to deck]

Thank to Karen Hsieh [Link to Miro board] 😍

Data Quality Issue across Data Pipeline

Data Quality Issue across Data Pipeline 💣 👻 👻 👻 ⚠ errors happened here data a ff ected data a ff ected data a ff ected business impact

Data Quality Issue across Data Pipeline ⚠ ✅ ✅ ✅ ✅ ✅ ❌ ❌ ❌ ✅ ✅ ❌

Data Reliability Automated https://www.piperider.io/

PipeRider: Data Reliability Automated https://www.piperider.io/ • PipeRider ensures data reliability through automating data testing and monitoring • Key Features • Instant quality assessment in HTML report • Report comparison • Extensible custom assertions • Works with existing dbt projects • Automatic test recommendations

How to use # install 
 $ pip install -U piperider # init piperider inside your project 
 $ piperider init # run and generate report 
 $ piperider run # compare different reports over time 
 $ piperider compare - reports

Assertions Column Assertions - assert_column_exist - assert_column_in_types - assert_column_min_in_range - assert_column_max_in_range - assert_column_not_null - assert_column_null - assert_column_type - assert_column_unique Table Assertions - assert_row_count_in_range Customize assertions by writing plugins: 
 https: / / docs.piperider.io/data - quality - assertions/custom - assertions

Integrate with dbt https://github.com/dbt-labs/dbt-core dbt enables data analysts to custom-write transformations through SQL statements. piperider integrates with your dbt project so you can init with zero setup. dataSources: - name: my_dbt_project type: postgres dbt: prof i le: my_dbt_project projectDir: . # the path to dbt_project.yml prof i lesDir: ~/.dbt # the path to the directory of dbt prof i les.yml …

Report

Comparison

CI Integration GitHub Actions as example https://docs.piperider.io/how-to/github-action

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DEMO Data Source: Video Games Sales Dataset

Roadmap https://github.com/infuseai/piperider • better report formats • better assertion recommendations • serve command to run a local web server • more integrations like AWS redshift

Thank You business@InfuseAI.io https://piperider.io