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fixed the broken link for pipes.md #381

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Jul 7, 2022
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fixed the broken link for pipes.md #381

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e43e620
fixed the broken link for pipes.md
shefalika-thapa Jul 7, 2022
d6b4272
fixed the broken link for pipes.md
shefalika-thapa Jul 7, 2022
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8 changes: 3 additions & 5 deletions README.md
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Expand Up @@ -51,20 +51,18 @@ Check the [step by step guide](https://docs.zingg.ai/zingg/stepbystep) for more

## Connectors

Zingg connects, reads and writes to most on-premise and cloud data sources. Zingg runs on any private or cloud based Spark service.

Zingg connects, reads and writes to most on-premise and cloud data sources. Zingg runs on any private or cloud based Spark service.
![zinggConnectors](assets/zinggOSS.png)

Zingg can read and write to Snowflake, Cassandra, S3, Azure, Elastic, major RDBMS and any Spark supported data sources. Zingg also works with all major file formats like Parquet, Avro, JSON, XLSX, CSV, TSV etc. This is done through the Zingg [pipe](docs/pipes.md) abstraction.
Zingg can read and write to Snowflake, Cassandra, S3, Azure, Elastic, major RDBMS and any Spark supported data sources. Zingg also works with all major file formats like Parquet, Avro, JSON, XLSX, CSV, TSV etc. This is done through the Zingg [pipe](docs/dataSourcesAndSinks/pipes.md) abstraction.
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@sonalgoyal I have changed it to docs. Please check.


## Key Zingg Concepts

Zingg learns 2 models on the data.

1. Blocking Model

One fundamental problem with scaling data mastering is that the number of comparisons increase quadratically as the number of input record increases.

One fundamental problem with scaling data mastering is that the number of comparisons increase quadratically as the number of input record increases.
![Data Mastering At Scale](/assets/fuzzymatchingcomparisons.jpg)


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