Apache Spark™ as a Service
Enable many users across the Organization with Apache Spark as a Service
Apache Spark is being extensively used to power the compute today in most organizations. Apache Spark can process both Streaming and Batch Data, perform complex ETL and Machine Learning.
Providing Apache Spark as a Service is very powerful. This way various users can access the data and compute available and perform Analytics, ETL and Machine Learning. However the challenge today is that users access Spark today by either writing complex Spark code or are limited to using SQL on Spark.
Fire Insights provides the perfect, most powerful layer on Apache Spark to enable Self-Service. Users can now log in with their Browser, access their data, and immediately start performing complex compute and machine learning on Spark.
Access Data and Compute through your Browser
With Fire Insights, users can simply log in through their browser. Adding new users to the system is very easy and it scales to hundreds of users.
Once users log in, they can immediately:
Start Browsing their data
Perform Data Prep and ETL
Perform Machine Learning
Visualize their data
Read data from their favorite systems and write data to systems.
Perform Data Preparation, Analytics/ML with Ease
Fire Insights makes is really easy to perform Data Preparation & Powerful Analytics.
Fire Insights has a number of Processors for:
Reading data in a variety of formats.
Validation and preparing the data in various ways
Performing Analytics and Machine Learning.
Perform Complex Dedup
Fire Insights makes it very easy to perform Complex Dedup.
Big Data is a place where many, many datasets come together from a variety of sources. Not all of the datasets are tied to each other with a unique key. Hence the Dedup becomes a common use case.
Fire Insights provides multiple powerful processors for performing dedup and matching of documents. They allow selecting from a variety of distance algorithms, applying different weights to various column etc.
Perform Streaming Analytics
Building Streaming Analytics systems are in general very difficult.
Fire Insights makes is seamless to build out and run Streaming Applications. Read data from streaming sources Apache Kafka/Amazon Kinesis etc., do the transforms/analytics and save the results into the appropriate store.
Fire Insights enables building complex streaming jobs in minutes and running them immediately onto a Cluster.
Load Data into various Stores
With Fire Insights loading data into various stores is fast and simple. Simply connect the data to a Data Store Processor, configure it for the right parameters and you are done.
Fire Insights provides a number of connectors out of the box including:
If any connector is not available, contact us for it. You can also add your own connector to Fire Insights and start using it.