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:
Needless to add, Striim is designed as an enterprise-grade platform, one that is highly secure, reliable and scalable.
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.
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.
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:
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
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.
By Uma Raj
By Uma Raj
By Abishek Balakumar