Data processing has become the key part of modern applications. Not only processing the data, but also visualizing data in a meaningful way is vital for making business decisions in an enterprise application.
With the rise of massive data storages and the speed of data generation, effective data processing architectural patterns came into industrial standards.
In the era of big data processing where data generated in high volume, variety, velocity, veracity and value; there are many architectural patterns that industrial applications are following for data processing. Lambda, Kappa and Zeta are some patterns used for real time big data processing.
Let’s take a look on how Lambda architecture can be adopted with the products and services comes with Microsoft Cortana Intelligence Suite.
What is Lambda Architecture?
Lambda architecture is a data processing architecture designed to handle massive quantities of data by taking the advantage of both batch and stream processing methods. Nathan Marz introduced the term of Lambda Architecture (LA) for having a generic, scalable and fault tolerant data processing architecture.
LA contains different layers which handles data in various methodologies in the process of data processing.
The ability of processing both batch data and real-time data streams is one of the significant features of lambda architecture.
What is Cortana Intelligence Suite?
Cortana Intelligence Suite is the Microsoft’s umbrella branding for fully managed business intelligence, big data and advanced analytics offerings comes with Azure cloud which enables businesses to transform the data into intelligent actions. So “Cortana” is there in this name. Then what? Is this related to the smart assistant comes with Windows 10? As Microsoft says, Cortana symbolizes the contextual intelligence that the solutions hope to deliver across the entire suite.
Cortana Intelligence Suite comes with the following services that specially designed for following tasks.
- Information Management
- Big Data Stores
- Machine Learning & Analytics
- Dashboards & Visualizations
How Cortana Intelligence Suite aligns with Lambda architecture?
Cortana Intelligence Suite (CIS) comes with different solutions that can cater both batch data sources and data streams. It is a significant improvement where you combine traditional batch processing systems and data stream analysis systems.
For an example think of a system that indicates the fuel level, oil levels, car tire pressure etc. of a vehicle… The system too should have the ability to analyze the data fetching from the IoT sensors real time as well as do predictions using the stored batch of data. CIS comes handy with various approaches to design this system with lambda architecture.
IoT sensors creates hundreds or maybe thousands of data points for a second. Handling such data streams and directing them to analytics flows can be done using Event Hubs(https://azure.microsoft.com/en-us/services/event-hubs/). you can use Azure Stream Analytics to get data from EventHub into Azure Storage Blobs. Thereafter you can use Azure Data Factory (ADF) to copy data on a scheduled basis from Blobs to Azure Data Lake Store. ADF can act as the batch data source. For analyzing and to build predictive models on the batch data HDInsight & Azure Machine Learning is the option you can go with. Azure SQL data warehouse can be used to store the analyzed data and visualizing them using PowerBI can be done. This is the batch data processing line.
In the line of real time data analysis, you can push the data stream coming from event hub to a Stream Analytics service or for an azure machine learning model. Visualizing data with PowerBI would come handy too.
Apart from the above explained components comes for data processing task, Microsoft Cognitive services can be used for transforming the user interaction for more human side. For an example, Bot framework and LUIS can be used with Bing speech API to provide voice commands for applications. Cortana skills can be used for enabling your app to deal with Cortana assistant.