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Analytics

Comprehensive Analytics for Today’s Connected Enterprise

The Internet of Things, mobile devices, and web apps generate large volumes of data in high velocity and variety. Unlocking this data helps to serve customers better, create new business and revenue models, and drive greater efficiencies across your enterprise.

A complete platform for data analytics, the WSO2 Analytics Platform revolutionizes the way you understand and work with your data. Combining the ability to analyze the same data at rest and in motion with predictive analysis, you can turn your data into enhanced business intelligence and greater opportunities. At the same time, the platform offers the flexibility to scale to millions of events per second, whether running on-premises and in the cloud.

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The Power of One Platform

Collect Data

First you define streams. Streams are a description of how your data will look like (Schema). Think it as a create table for RDBMS.

One Sensor API to publish events for both batch and realtime pipelines.

Analyze & Make Decisions

Write Queries - Write SQL like Queries using Spark SQL and Siddhi Event Query Language using Streams you have defined when publishing events

Use WSO2 Machine Learner Wizard to create Machine Learning Models, compare them side by side, and select the best model.

Communicate

Communicate your outputs to the end user as alerts, visualizations, and APIs.

Visualize - given the “Overall idea” in a glance (e.g. car dashboard), supports personalisation, you can build your own dashboards, and supports drill down.

Combining Real-time and Batch Analytics in One Powerful Platform

Collect data once, process it in many ways

A single API is sufficient to collect data and process it for batch, real-time, and even interactive and predictive analytics.

Incorporating the Lambda Architecture

The Lambda Architecture supports a variety of applications that need to run with low latency, along with allowing for different logic to be applied in the real-time and batch layers.

Analytics at the edge

Aggregating data at the point of origin facilitates the ability to detect important trends or aberrations, and also significantly reduces network traffic to improve performance.

Enhance Business Intelligence with Interactive Analytics

On demand analysis of data

Once data is collected or batch processed, you can further investigate into your data using simple search queries via Apache Lucene in an interactive way.

Selective deep analysis

Detect an anomaly using real-time processing, followed by deep analysis using data stored in batch processing (e.g. Fraud detection, and offering snap deals)

Effective Decision Making with Predictive Analytics

Discover “logic” from examples where such logic is complex

Build “a model” using machine learning algorithms applied to historical data. (e.g. fraudulent and non-fraudulent transactions, and use that model to detect fraudulent transactions)

Build and integrate machine learning models in many ways

Build machine learning models from large datasets via WSO2 Machine Learner or using R, a widely used language for statistical computing. The models can be incorporated into your business logic with WSO2 CEP or WSO2 DAS for predictive analysis.

Explore data visually

Data is visually presented to easily co-relate and select best data points and algorithms for building better prediction models.

High Performance and Availability

Built on the fast performance of the open source Siddhi CEP engine developed by WSO2, the Analytics Platform can process 100K+ events per second and is one of the fastest realtime processing engines around.

The WSO2 Analytics Platform leverages Apache Spark to scalably batch-process large amounts of data in-memory and to build machine learning models for predictive analytics.

Development and Deployment Flexibility

Easy to use SQL-like query language for real-time and batch processing along with text based querying for interactive analytics and guided wizards for predictive analytics.

Apache Storm, the open source real-time computation system, provides greater scalability by enabling multiple events and streams to run in parallel.

Customizable dashboard to visualize real-time and batch results, with configurable gadgets.

The entire WSO2 Analytics Platform is fully open source and available under the Apache License 2.0

Analytics

Success Stories

In today’s world, modern businesses constantly receive large volumes of data. Guesswork is no longer sufficient - in the highly efficient world of connected business, accurate data analysis is critical to the process of deriving information for the future.

Since 2009, WSO2’s products have been tackling the task of analyzing complex business data. Today, clientele in the calibre of Fortune 500 enterprises continue to leverage and endorse the WSO2 Analytics platform to get the most of their data.

Enabling Access to Enterprise Insights

Many organizations collect data and information - and at some point, their business models rely on communicating insights to consumers. This is often a major roadblock in the business process: organizations, often lacking a single end-to-end solution, frequently rely on multiple systems and complex human operation to handle these routine tasks, introducing significant delay.

By leveraging the power of the WSO2 Analytics platform, organizations have been able to share data and information quickly, effectively and efficiently.

Tackling the Problem of Big Data

One of the inherent challenges of big data is the difficulty in analysing it. Not only are robust analytics tools needed, but these tools also need to be flexible and versatile enough to handle any kind of data and any kind of processing requirement, be it batch, real-time or even predictive analysis. Added to this is the requirement of handling all manner of processing rules as different data specific to leads to different insights that are often entirely specific to the context of the organization. Speed is always of the essence.

WSO2’s suite of offerings - the Data Analytics Server (formerly Business Analytics Monitor), Complex Event Processor and Machine Learner components have been put to use in a variety of complex use cases, many of them in complex high-speed response situations that process and output vast torrents of data for real-time insights.

Building Data-Heavy Technological Ecosystems

Massive projects often transcend single applications and become complex ecosystems of applications woven together into a distributed service architectures. Because of the flexibility of the WSO2 platform, our clients have been readily able to connect to and gather insights from anything - be it a new SOA deployment with other technologies, middleware and APIs in the stack, or a collection of IoT devices, or legacy systems working together.