Real-Time Data Integration using Striim

Data Explosion is a reality today. Enterprises have access to vast amounts of “big data” from multiple sources. Leaders are running analytics models on this data to gather insights – to spot both opportunities and threats.

But, that’s not all. There is also an explosion of real-time data coming in, and unless you adopt “Streaming Analytics” to instantly draw insights, you may miss out on spotting opportunities or tackling threats ahead of time. The point is, running batch-mode analytics alone is no longer sufficient.

“Streaming Analytics” can also help mitigate risks from fraud or security breaches. Moreover, one of the key advantages of gathering real-time actionable insights revolves around the ability to capture data that changes.

The Striim Platform automates the process of capturing time-sensitive insights to provide immediate intelligence that can impact the following:

  1. Spot critical fraud or security breaches
  2. Spot major changes or trends than can in-turn help you spot opportunities and act instantly with modified marketing campaigns or strategies
  3. Identify risks and critical events that can impact both short-term and long-term strategy

Needless to add, Striim is designed as an enterprise-grade platform, one that is highly secure, reliable and scalable.

Learn more about Indium’s Strategic Partnership with Striim

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At Indium Software, we’re an authorized implementation partner of Striim.

We’ve worked with a range of clients including banks, financial institutions and retail & e-commerce companies, helping them with Striim implementation. Recently, we worked with one of the world’s leading banks, helping its digital banking division with Real Time data integration using Striim. We had to move a massive database from Oracle to GCP, with a Striim agent handling Change Data Capture (CDC) and real-time integration that was highly secure.

Potential Use Cases for Striim Implementation

The potential of use for this analytical application is unlimited. From the energy sector to banking and financial, ecommerce, airlines and healthcare, real-time analytics can help in improving service levels, strategy formulation as well as prevent potential threats to almost any business with massive real-time data.

  • It can be used in the energy sector to capture power outages – and then help with preventing them or restore services on priority – by using real-time intelligence
  • In the banking, insurance & financial sector, it can help enable risk-based, real-time policy pricing to reduce exposure; detect and prevent fraud, AML compliance; improve regulatory compliance; provide bespoke solutions to customers based on their real-time search data; and streamline ATM operations through remote monitoring and predictive maintenance
  • In the transport and logistics sector, it can provide greater visibility into operations in real-time; ensure timely delivery and reduce fuel costs by optimizing fleet routes and planning staff utilization better; implement predictive maintenance and thereby extend the lifespan of the assets;  enable real-time tracking of vehicles; improve warehouse capacity utilization through real-time inventory data analytics
  • For the aviation sector, use cases revolve around getting real-time updates on weather, flight delays and other such events to optimize crew and staff planning and flight schedules; track aircraft parts and rapidly submit work orders; improve real-time staffing decisions depending on actual passenger load; reduce immigration and customs lines; provide relevant and meaningful rewards for customer loyalty
  • As you can see from above, the use cases are endless. The key aspect is to run streaming analytics on a proven, secure, scalable platform like Striim.

The ‘Striim – Indium Software’ Value Proposition

Striim uses a combination of filtering, multi-source correlation, advanced pattern matching, predictive analytics, statistical analysis and time-window-based outlier detection to aggregate all relevant data.

By querying the streaming data continuously, it quickly and accurately identifies events of interest and provides a deep perspective into operations by performing in-flight enrichment.

It sends automated alerts, triggers workflows, publishes results to real-time, interactive dashboards and distributes data to the entire enterprise.

Striim continuously ingests data from a variety of sources such as IoT and geolocation. It uses advanced pattern matching, predictive analytics and outlier detection for comprehensive streaming analytics. The analytical applications can be easily built and modified using SQL-like language and wizards-based development.

Indium Software, an authorized implementation partner of Striim, has deep expertise and experience in leveraging the Striim platform for the following processes:

  • Real Time Data Integration
  • Hybrid Cloud Integration
  • Streaming Analytics
  • GDPR Compliance
  • Hadoop and NoSQL Integration

    A cross-domain expert with over 20 years of experience in several industries such as retail, BFSI, e-commerce, healthcare, manufacturing, gaming among others, Indium Software is well-positioned to handle a wide range of Big Data services across Data Engineering and Data Analytics.

    Recently, we completed a Data Integration project for a leading bank, helping move their data from Oracle database to Postgres in Google Cloud Platform.

    The architecture implemented included effective data monitoring and customised visualization of the streaming data. Additionally, alerts were created when multiple data pipelines were being accessed simultaneously.

    Additionally, Indium helped a client with the implementation of Striim in their messaging queue platform. With this setup, the client could stream data in their Kafka queue and write data into the Kafka logs using Kafka writer, which could then be consumed by multiple downstream systems and applications

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    The Indium team aided in supporting another customer through an open processor (custom scripts) in Striim to provide a data audit feature for every transaction hitting the database. The changes were then updated in a log database, enabling tracking of the data change, for example insert, delete and update. Additionally, our team created another open processor in moving the current system time forward by 7 hours, before replicating the timestamp column in the database.

    Give us a shout, if your business generates real-time data. We’ll seamlessly create an automated process to draw insights from this real-time feed. We can also certainly help with any of the other aspects of Striim implementation.