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Real-Time Streaming Analytics | Informatica Consulting

  • IoT and Streaming Data are progressively leading the same path as challengers to intensify operational productivity, better customer satisfaction and real-time verdict. As per Gartner, “More than half major organizations and business systems will assimilate continuous intelligence that includes real-time context data for improving the decision-making.” Adopting Informatica Consulting will ensure businesses are future-ready.


    Streaming and IoT data management have the capability to manage, ingest and act on diverse real-time data. Apache Spark delivers tremendous scaling ability and has introduced Structured Streaming recently to solve cases of real-time streaming analytics. In addition to this, the endorsement of data lakes and computing services that are cloud-based, expanding massively. Also, Databricks are providing scalable engines that are able to develop and operate a huge amount of data.



    Leading Streaming Use Cases by Customers


    The consumers recognized these two Streaming cases:


    1. Select a file and load the data onto a data lake to use it for data science and advanced analytics projects.
    2. Run in-built predictive models on streaming data because data runs through the flow in real-time for extortions.


    Starting from ingestion of streaming and IoT data to interpretation of data, and then acting on streaming data, Informatica provides ultimate streaming data management. Everything is provided on a single platform to facilitate the customers for not using different channels for clusters and streaming.


    Let's review how Informatica's management solutions can solve those leading use cases of customers:


    The very first step to solve the streaming use case is to ingest the IoT data from different sources into a data lake. Let's take an example of ingesting streaming data from IoT sources in both Kafka and a data lake.



    Informatica implements cloud-ready and cloud-native streaming and IoT data ingestion solutions from streaming sources Kafta, IoT, weblogs, etc. into cloud data lakes.  Informatica's Edge Data Streaming (EDS) and Ingestion at scale offers a great experience for designing the workflow and real-time auditing and controlling to manage the jobs.


    Batch Processing


    It is the utmost requirement to mature the raw IoT data for integration with different aggregations and transformations.  Informatica's Big Data Management (BDM) using Databricks makes the raw data presumable to be used directly by data scientists and analysts. Databrick offers cloud computing services for processing huge amount of data without managing to compute clusters.


    Real-Time Analytics


    We need to do real-time enhancements on the data to enable it to work under machine learning models efficiently, and then we can solve the real-time analytics use case. Informatica Big Data Streaming (BDS), a cloud-based continuous stream processing solution parses the real-time analytics use cases with Spark Streaming engine for doing analytics on streaming data.




    Informatica offers a cloud-based data management platform for batch processing and solving streaming by using cases from their customers. Big Data Streaming and Management use the same interface, which makes it easier for customers to do batch streaming rather than to develop and monitor from different sources.


    Informatica Consulting helps developers to leverage business sense and  further their understanding about batch and streaming scaling with zero learning curve. ExistBI are Informatica partners with services in the US, UK and Europe.