Sparkflows Big Data Use Cases

Below are some of the top big data use cases easily enabled by Sparkflows

Each of these use cases will take less than 30 mins with Sparkflows

Self-Serve Big Data Analytics

 

Accomplish Big Data Analytics with Drag & Drop with 100+ building blocks

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Machine Learning

 

Perform Machine Learning on huge datasets with drag and drop

NLP  

Perform NLP on Big Data with OpenNLP & StanfordNLP

Log Analytics

 

Build Log Analytics Platform with Kafka, Spark, Solr/Elastic Search, Hue

Entity Resolution

 

Perform large scale Entity Resolution on data from multiple channels

Dashboards

 

Create Rich Dashboards from the output of various workflows

ETL Pipelines
 

Build ETL pipelines with ease. Also incorporate SQL, Scala, Jython in it.

Streaming Analytics

 

Perform Streaming Analytics reading from Kafka,performing complex transformations, generate graphs and write out to Solr, Hbase etc.

OCR

 

Perform OCR on millions of images with Tesseract

Loading Data into ES, Solr and HBase

 

Easily load data into Elastic Search, Solr, HBase etc.

Format Conversion

 

Convert Big Data from one format to another

Hadoop Small Files Problem

   

Easily merge small files and create large ones

Self-Serve Big Data Analytics:  Accomplish Big Data Analytics with Drag & Drop with 100+ building blocks
ETL Pipelines:  Build ETL pipelines with ease. Also incorporate SQL, Scala, Jython in it.
 
 
NLP:  Perform NLP on Big Data with OpenNLP
OCR:  Perform OCR on millions of images with Tesseract
Streaming Analytics:  Perform Streaming Analytics reading from Kafka, performing complex transformations, generate graphs and write out to Solr, Hbase etc.
Machine Learning:  Perform Machine Learning on huge datasets with drag and drop
 
Entity Resolution:  Perform large scale Entity Resolution on data from multiple channels
Log Analytics:  Build Log Analytics Platform with Kafka, Spark, Solr/Elastic Search, Hue
Format Conversion:  Convert Big Data from one format to another
Loading Data into Solr, ES and HBase:  Easily load data into Solr, Elastic Search, HBase etc.
Hadoop Small Files Problem:  Easily merge and save large number of small files
Custom Nodes: Create & Use Custom Nodes which add custom features
Dashboards: Combine output of various Workflows/Nodes into a Dashboard

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