Power your analytics with Sparkflows
Instantly Deliver Agile Analytics to Clients
Sparkflows can power your Advanced Analytics to Clients.
Sparkflows provides a Visual Advanced Analytics Studio, which fully integrates with you systems.
Alternative data sources and customer-owned data sources
Secure, flexible and scalable
Access to B2B data and analytics
Expertise and consultative services
Advanced analytics tools
Use predefined Sparkflows analytics functions or code your own
Fire Insights fits right into your advanced analytics platform. It provides the visual studio to enable users to prepare to seamlessly prepare data, perform analytics, build ML models and evaluate and store them.
Fire Insights integrates with your analytical studio. With single sign off - SSL, the users are able to login seamlessly into Fire Insights.The look and feel of Fire Insights is updated to fit right into the look and feel of your platform. Fire Insights integrates with your existing compute and storage to provide analytics to the users.
Self Serve Data Preparation with Fire Insights
With Fire Insights , the users get self serve data preparation features. Fire provides a powerful workflow editor for the users to build the data preparation pipelines. Fire also has 280+ processors for the users to drag and drop and prepare the data and store it.
Fire Insights provides powerful analytics features for the users to perform advanced analytics. They can explore the data, view .......,
view distribution of the datasets etc. etc.
Fire provides extensive feature generation and Machine Learning Model Processors for the users to easily create Regression, Classification and Clustering Models. Fire has 80+ processors for complex feature generation and Machine Learning building.
Sparkflows enables you to quickly build out your pipelines for simple to most complex of requirements. Deploy them with one click on any of your Big Data Environment - whether you are on the cloud or on-premise.
You do not have to worry about version upgrades of your infrastructure or backward compatibility.
Advanced Analytics Platform
Sparkflows provides rich capabilities for Data Quality.
Sparkflows uses machine learning-enabled de-duplication, validation, and standardization methods to clean data for the highest quality for the multi data operations. Data is enriched in various ways.
Sparkflows has built-in processors for statistical analysis of data values to evaluate frequency, distribution and completeness of data. eg. Histograms etc.
Data profiling & discovery
Various inbuilt algorithms( eg. Jarowrinkler, Levenstein etc.) for data comparison so that similar but slightly different records can be matched. Dedup processors for removing duplicates.
Data matching & De- Duplication
Various in-built processors for validating email addresses , range of values, dates etc.
Innovate with your own Processors
Sparkflows is extendable for your environment. Add more processors based on your needs. Sparkflows integrates with the modern data stack.
Sparkflows Processors have schema propagation, interactive execution, scale to petabytes of data and can also provide visualizations.
Speed up Data Analytics with fast Data Preparation
Data analysts spend up to 80% of their time cleaning data instead of analyzing it. Speed up data preparation time 10-30x faster with Sparkflows.
With Interactive Execution, view the output of any processor instantly, thus quickly iterating to get your data to a clean state. With powerful data validation rules, seamlessly validate and drop invalid records.
Deploy and Run
Run your workflows with one click, schedule them or trigger them by event. Easily view the results of past executions.
Or run them with the scheduler of your choice as Sparkflows is an open system.
Easily scale horizontally to petabytes of data. Sparkflows also allows you to control the persistence level of DataFrames, execution parameters etc. to ensure you are not limited in any way.
Sparkflows processors are written to run at extreme scale. Save millions of dollars by running faster with efficient algorithms.