Data Science & Analytics
Self-Service Data Science and Analytics for Enterprise
What makes Sparkflows Data Science & Analytics Platform Different
Sparkflows is the most powerful Self-Serve Data Science and Analytics product purpose-built for the enterprise. Seamlessly connect to your data from a wide variety of data stores, clean, enrich it, and build best-in-class machine learning models using the machine learning library of your choice and deploy them on any of the public clouds.
Sparkflows scales seamlessly from megabytes to petabytes despite being fully extensible. Add custom processors, time-series feature generation, data cleaning, or machine learning to fit your needs. Seamlessly onboard hundreds of users onto the platform and enable collaboration to build advanced data and machine learning solutions.
Create workflows with 250+ prebuilt processors, or code in with the language of your choice - Python, Java, Scala or SQL.
Machine Learning Accelerated
Prepare and Enrich
Analysts and Data Scientists need to bring multiple types of disparate data sources together to effectively answer questions.
Sparkflows takes a different approach by offering data prep and data enriching capabilities through an intuitive user interface that is up to 100 more responsive than traditional approaches.
Access all your relevant Data
Connect to and cleanse data from data warehouses, cloud applications, spreadsheets, and other sources.
Prepare and blend the right Data
Create the right dataset for analysis or visualization using data quality, integration and transformation tools.
Model & Predict
Generate complex features for your model building using built in Processors.
Build your ML/AI models seamlessly using Apache Spark ML, SageMaker, scikit-learn etc.
Code in Python, Scala, SQL or Jython. Use from a library of 80+ ML Processors
Execute your Jobs with one click. View results of past executions, deploy your models etc.
Model and Predict by building Workflows
Traditional and legacy predictive analytics are based on complex, difficult-to-use coding platforms that are mostly inaccessible to data analysts.
Sparkflows makes predictive analytics accessible to every analyst. With repeatable workflows that deliver the self-service data analytics capabilities required for predictive analytics, analysts can create models with drag-and-drop tools.
Also code in SQL, Python, Scala scaling to your cluster within the workflows. Or build reusable Processors data preparation, feature generation and modeling to be made available for everyone.
Validate the results of predictive models.
Make predictive analytics easier and faster by eliminating the traditional, static reports and using interactive visualizations to validate model results.
Visualize and Dashboard Results
With powerful charting capabilities of Sparkflows, bring your data to life. Combine various charts into dashboards.
When running with streaming jobs, seamlessly create streaming charts.
Interact with your data with interactive dashboards.
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.
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.
Save, Load and Deploy your ML models.
Sparkflows is a collaborative data science and analytics platform. Teams can work together to build Applications. Data Analysts, Data Scientists and Data Engineers can iterate, build and deliver data products seamlessly.
Multiple groups with different permissions can work together on an Application in Sparkflows. From preparing data to analytics to building predictive models to visualization and dashboards, users can seamlessly accomplish them in an Application.
Integrate with your other systems using the powerful REST API's. Create workflows, run them, view models and execution results using the REST API's.
Perform Predictive Analytics
Deploy & Run
Predict with modern ML Technologies
Provides algorithms developed from the ground up for distributed computing.
Random Forest, GLM, GBM, XGBoost, GLRM, Word2Vec and many more.
Spark ML makes practical machine learning scalable and easy.
Logistic Regression, Decision Tree, Random Forest, Gradient Boosted Tree, Multi-layer Perceptron and many more.
Provides extensive Machine Learning in Python
SVM, Nearest Neighbors, Random Forest, SVR, Ridge Regression, Lasso, K-Means, Spectral Clustering, Mean-Shift and many more.
Provides fully managed Machine Learning System.
Apache MXNet, TensorFlow, PyTorch, and Chainer.Scikit-learn and SparkML by providing pre-built Docker images.