With Panopticon Streams, users now able to create sophisticated Kafka data flows quickly and easily with no coding BEDFORD, Mass., Oct. 16, 2018 (GLOBE NEWSWIRE) -- Datawatch Corporation (NASDAQ-CM: DWCH) today announced the general availability of ...
With Panopticon Streams, users now able to create sophisticated Kafka data flows quickly and easily with no coding
BEDFORD, Mass., Oct. 16, 2018 (GLOBE NEWSWIRE) -- Datawatch Corporation (NASDAQ-CM: DWCH) today announced the general availability of Panopticon Streams, a stream processing engine built on the popular Apache Kafka platform. Whether used as a stand-alone solution or in conjunction with Panopticon’s Visual Analytics platform, enterprises benefit from comprehensive monitoring and analysis of real-time streaming and time series data. Panopticon’s unique solutions enable business users who deployed web-based solution to build sophisticated Kafka data flows with no coding.
With Panopticon Streams, users connect directly to a wide range of streaming and historic information sources, including Kafka, Kx kdb+, Solace, Hadoop and NoSQL sources. The platform supports critical data functions including:
- Streaming Data Prep: Combines multiple real-time streams with historic data sources
- Calculation Engine: Calculates performance metrics based on business needs
- Aggregation Driver: Combines data as needed
- Alerting Engine: Highlights anomalies against user-defined thresholds
- Integration with the Confluent Enterprise Control Center
- Expanded support for IoT environments, including manufacturing, energy/utilities, and transportation/logistics
“The introduction of Panopticon Streams gives our customers a true streaming analytics platform optimized for businesses working with continuously changing operational data,” said Peter Simpson, vice president of visualization strategy at Datawatch Panopticon. “In particular, our Capital Markets customers will benefit from its support of several key use cases, including best execution, real-time P&L, transaction cost analysis and trader and trading surveillance.”
Forrester analyst Mike Gualtieri noted in his The Forrester Wave™: Streaming Analytics report that, “Streaming Analytics is essential technology to orchestrate interactions between a complex portfolio of applications and the data sources."1 He also noted in his Prescriptive Analytics: The Black Belt Of Digital Decisions report that, “Streaming Analytics can provide real-time insights for decision logic or it can detect patterns in data that indicate that a decision must be made.”2
As with Panopticon Visual Analytics, Panopticon Streams requires no coding expertise. Users who understand the business problems can create their own data flows, which can utilize information from any number of sources and incorporate joins, aggregations, conflations, calculations, unions and merges and alerts. Analysts can then visualize processed data using Panopticon Visual Analytics and deliver it to Kafka, Kx kdb+, InfluxDb, or any SQL database.
Simpson continued: “The addition of Panopticon Streams’ capabilities means we now offer a general purpose streaming analytics platform. It has applications anywhere organizations need to identify anomalies and outliers, investigate their causes, back test potential solutions, and then alter their business processes to address the issue. Given the software’s ability to handle real-time and time series data, we believe it will be most useful in telecommunications, energy, and IoT applications, in addition to electronic trading for capital markets firms.”
The company will demonstrate Panopticon Streaming Analytics at the Kafka Summit in San Francisco on October 16 and 17, 2018. More details: https://kafka-summit.org/events/kafka-summit-san-francisco-2018/
The company is also hosting a full day interactive workshop focused on implementing Panopticon Streaming Analytics in Kafka environments in London on October 30, 2018. More details: //viz.datawatch.com/l/62102/2018-09-28/36sk628
To learn more about Panopticon Streams, visit: www.panopticon.com or call 978-441-2200.
Leading capital markets firms rely on Panopticon from Datawatch for faster analytics of real-time streaming and time series data. The powerful combination of stream processing, rapid data comprehension through visual analysis, faster investigation through time series analysis, and playback down to the individual tick supports organizations in making timely, more informed decisions that have immediate financial impacts. For more information about Panopticon and how it has been deployed at customers in time critical areas across trading, risk, compliance, trading operations and asset management, please visit: www.panopticon.com.
About Datawatch Corporation
Datawatch Corporation (NASDAQ-CM: DWCH) is the data intelligence provider with market leading enterprise data preparation, predictive analytics and visualization solutions that fuel business analytics. Only Datawatch can confidently position individuals and organizations to master all data – no matter the origin, format or narrative – resulting in faster time to insight. Datawatch solutions are architected to drive the use of more data, foster more trust and incorporate more minds into business analytics. Thousands of organizations of all sizes in more than 100 countries worldwide use Datawatch products, including 93 of the Fortune 100. The company is headquartered in Bedford, Massachusetts, with offices in New York, London, Toronto, Stockholm, Singapore and Manila. To learn more about Datawatch please visit: www.datawatch.com.
Safe Harbor Statement under the Private Securities Litigation Reform Act of 1995
Any statements contained in this press release that do not describe historical facts may constitute forward-looking statements as that term is defined in the Private Securities Litigation Reform Act of 1995. Any such statements contained herein, including but not limited to those relating to product performance and viability, are based on current expectations, but are subject to a number of risks and uncertainties that may cause actual results to differ materially from expectations. The factors that could cause actual future results to differ materially from current expectations include the following: rapid technological change; Datawatch’s dependence on the introduction of new products and product enhancements and possible delays in those introductions; acceptance of new products by the market, competition in the software industry generally, and in the markets for next generation analytics in particular; and Datawatch’s dependence on its principal products, proprietary software technology and software licensed from third parties. Further information on factors that could cause actual results to differ from those anticipated is detailed in various publicly-available documents, which include, but are not limited to, filings made by Datawatch from time to time with the Securities and Exchange Commission, including but not limited to, those appearing in the Company’s Annual Report on Form 10-K for the year ended September 30, 2015. Any forward-looking statements should be considered in light of those factors.
Vice President Worldwide Marketing, Datawatch Corporation
© 2018 Datawatch Corporation. Datawatch and the Datawatch logo are trademarks or registered trademarks of Datawatch Corporation in the United States and/or other countries. All other names are trademarks or registered trademarks of their respective companies.
1 The Forrester Wave™: Streaming Analytics, Q3 2017 (hyperlink to: https://www.forrester.com/report/The+Forrester+Wave+Streaming+Analytics+Q3+2017/-/E-RES136545)
2 Prescriptive Analytics: The Black Belt Of Digital Decisions (hyperlink to https://www.forrester.com/report/Prescriptive+Analytics+The+Black+Belt+Of+Digital+Decisions/-/E-RES122982)
Source(s) : Datawatch Corporation
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