ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
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Updated
Dec 24, 2024 - Python
ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
Python based Open Source ETL tools for file crawling, document processing (text extraction, OCR), content analysis (Entity Extraction & Named Entity Recognition) & data enrichment (annotation) pipelines & ingestor to Solr or Elastic search index & linked data graph database
AzLogDcrIngestPS - Unleashing the power of Log Ingestion API with Azure LogAnalytics custom table v2, Azure Data Collection Rules and Azure Data Ingestion Pipeline
Google Cloud Storage connector, pre-processor and model for predicting user search intent based on keywords
Google Analytics connector, pre-processor and model for predicting churning users for digital publishers.
My experiments with Apache Spark for Humans ⭐
DataStax or Cassandra Ingest from Relational Databases with StreamSets
Sample Azure Data Factory pipeline for ingesting Data Packages directly from the Download API of the Ordnance Survey Data Hub into Azure Storage.
Created a data pipeline using sqoop to ingest data from sql server into the hive table and used hive for feature engineering and analysis.
A Question Answering(Q/A) Chatbot on Insurance Documents. Powered by Retrieval Augmented Generation(RAG), LlamaIndex and LangChain. Inspired from my Upgrad_IIITB PG Course.
Ingest any format data into postgreSQL database
A real-life end-to-end cloud sub-system scenario
The multinational retail data contralisation project is a data warehousing project that focuses on ingesting data from disparate sources to create a centralised warehouse
Transform incoming AWS WorkMail email with Excel attachment to CSV and save to S3 bucket
A cryptho currency automated bot
A Question Answering(Q/A) Chatbot on Insurance Documents. Powered by Retrieval Augmented Generation(RAG) and LlamaIndex. Inspired from my Upgrad_IIITB PG Course.
A Question Answering(Q/A) Chatbot on Insurance Documents. Powered by Retrieval Augmented Generation(RAG), LlamaIndex and LangGraph. Inspired from my Upgrad_IIITB PG Course.
Código fuente: Análisis de Vuelos basado en trabajo de Valliappa Lakshmanan.
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