When dealing with payments, speed is king. Technology is increasing the speed at which innovation happens, and nowhere is that more apparent than how everyday commerce is transacted. Credit cards are now built with tap-to-pay capabilities, if you still even have a physical credit card. Phones have become the new credit card, with data from transactions and mobile banking adding to the overwhelming amount of data that can be collected.

The thing about data is there’s no end to how much of it you can collect and keep. Each day, if you’re like most of the global banks I work with, you’re generating oceans of the stuff. Yet the bulk of it will never be very helpful or even relevant to your day-to-day business decisions.

At the end of March, we released the first version of Cloudera SQL StreamBuilder as part of CSA 1.3. It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. Since then, we have been working hard to expose the full power of Apache Flink SQL and the existing Data Warehousing tools in CDP to combine it into a state-of-the-art real-time analytics platform.

Cloudera has been named as a Strong Performer in the Forrester Wave for Streaming Analytics, Q2 2021. We are excited to be recognized in this wave at, what we consider to be, such a strong position. We are proud to have been named as one of “The 14 providers that matter most” in streaming analytics. The report states that richness of analytics, development tool options and near-effortless scalability are what streaming analytics customers should look for in a provider.

In October of 2020 Cloudera acquired Eventador and Cloudera Streaming Analytics (CSA) 1.3.0 was released early in 2021. It was the first release to incorporate SQL Stream Builder (SSB) from the acquisition, and brought rich SQL processing to the already robust Apache Flink offering. The team’s focus turned to bringing Flink Data Definition Language (DDL) and the batch interface into SSB with that completed.

In a telecoms industry differentiated mainly by service and threatened by churn, gaining access to timely customer data initially drove internal demand for analytics and BI (ABI) reporting. When demand grew beyond customer service, our IT team really struggled to keep up. This set us off on a journey to find ways to help our colleagues to find insights and the answers to their questions themselves.