Month: April 2016

Striim Sponsors and Presents at Big Data Innovation Summit in SF

Posted on by Striim Team | 1 min read | 2 views

Striim is a proud sponsor at Big Data Innovation Summit SF, April 21-22 at the San Francisco Marriott Marquis Hotel. Join Striim’s Co-founder and CTO, Steve Wilkes, Thursday, April 21 at 9:30 a.m., as he discusses how to innovate your data strategy through streaming in his 30-minute presentation:

The Big One’s Coming!

Modernize Your Data Strategy Before It Hits

April 21 at 9:30 a.m.

San Francisco Marriott Marquis Hotel

in the Yerba Buena Ballroom

Security breaches and fraud. Increased customer churn. Halted manufacturing lines. Lost data. These are just some of the “data earthquakes” that signal a need to modernize your data strategy. But, unlike San Francisco’s imminent mega-quake, these outcomes can be prevented.

The key? Streaming integration. Join this session to learn why no innovative data strategy is complete without streaming integration, and how this can be applied to solve the critical use cases of today and tomorrow.

Exhibition Hours:

  • Thursday, April 21, 8:30 a.m. – 5:30 p.m.
  • Friday, April 22, 8:30 a.m. – 4:45 p.m.

We look forward to seeing you at Big Data Innovation Summit!

Real-Time Financial Transaction Monitoring

Posted on by Steve Wilkes | 2 min read | 2 views

 

 

Financial Monitoring Application

Building complex, financial transaction monitoring applications used to be a time-consuming task. Once you had the business case worked out, you needed to work with a team of analysts, DBAs and engineers to design the system, source the data, build, test, and rollout the software. Typically it wouldn’t be correct the first time, so rinse and repeat.

Not so with Striim. In this video you will see a financial transaction monitoring application that was built and deployed in four days. The main use case is to spot increases in the rate at which customer transactions are declined, and alert on that. But a whole host of additional monitoring capabilities were also built into the application. Increasing decline rates often indicate issues with the underlying ATM and Point of Sale networks, and need to be resolved quickly to prevent potential penalties and decline in customer satisfaction.

The application consists of a real-time streaming dashboard, with multiple drill-downs, coupled with a continuous back-end dataflow that is performing the analytics, driving the dashboard and generating alerts. Streaming data is sourced in real time from a SQL Server database using Change Data Capture (CDC), and used to drive a number of analytics pipelines.

The processing logic is all implemented using in-memory continuous queries written in our easy to work with SQL-like language, and the entire application was built using our UI and dashboard builder. The initial CDC data collection goes through some initial data preparation, and is then fed into parallel processing flows. Each flow is analyzing the data in different ways, and storing the results of the processing in our built-in results store to facilitate deeper analysis later.

If you want to learn how to build complex monitoring and analytics applications quickly, take 6 minutes to watch this video.

 

Back to top ⇧