Steve Wilkes talks with Dave Vellante at Big Data SV 2018 at the Forager Eatery in San Jose, CA.
#BigDataSV #theCUBE
https://siliconangle.com/2018/03/19/is-this-the-perfect-recipe-for-data-streaming-integration-and-analysis-bigdatasv/
Is this the perfect recipe for data streaming, integration and analysis?
Raw data can be compared with the raw ingredients for a gourmet dish. The potential is there, but it needs to be prepared correctly before being served up for consumption. Creating a successful platform for streaming integration analytics takes more than than stuffing things in and taking things out. And just as many chefs shout that their signature dish is the greatest, many technology providers advertise that they have the perfect end-to-end data streaming solution. But what does true end-to-end service look like?
“When you are thinking about doing streaming integration, it’s more than just moving data around,” said Steve Wilkes, (pictured) founder and chief technical officer of Striim Inc. “[You] can’t just give people streaming data; [you] need to give them the ability to process that data, analyze it, visualize it, play with it, and really truly understand the data.”
Wilkes spoke with Dave Vellante (@dvellante), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed Striim’s real-time data integration and streaming analytics platform, as well as what makes it a complete end-to-end solution.
From data collection to dashboard visualization
“The first part of being able to do streaming data integration or analytics is that you need to be able to collect the data,” Wilkes said. The Striim platform has wizards to help build data flows and create streams SQL-based processing for filtering, transformation, aggregation, and enrichment of data, as well as a cache component to load reference data into memory.
Apache Kafka open-source stream processing software comes built into Striim, and target adapters allow write-out to cloud storage, such as Amazon Redshift or Azure Blob Storage. Ready to analyze the data?
“So you take the data stream, you build another data flow that is doing some aggregation of windows, maybe some complex event processing, and then use that dashboard builder to build a dashboard to visualize all of that,” Wilkes concluded.
Watch the complete video interview with Wilkes below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event.
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Steve Wilkes, Striim | Big Data SV 2018
Steve Wilkes talks with Dave Vellante at Big Data SV 2018 at the Forager Eatery in San Jose, CA.
#BigDataSV #theCUBE
https://siliconangle.com/2018/03/19/is-this-the-perfect-recipe-for-data-streaming-integration-and-analysis-bigdatasv/
Is this the perfect recipe for data streaming, integration and analysis?
Raw data can be compared with the raw ingredients for a gourmet dish. The potential is there, but it needs to be prepared correctly before being served up for consumption. Creating a successful platform for streaming integration analytics takes more than than stuffing things in and taking things out. And just as many chefs shout that their signature dish is the greatest, many technology providers advertise that they have the perfect end-to-end data streaming solution. But what does true end-to-end service look like?
“When you are thinking about doing streaming integration, it’s more than just moving data around,” said Steve Wilkes, (pictured) founder and chief technical officer of Striim Inc. “[You] can’t just give people streaming data; [you] need to give them the ability to process that data, analyze it, visualize it, play with it, and really truly understand the data.”
Wilkes spoke with Dave Vellante (@dvellante), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed Striim’s real-time data integration and streaming analytics platform, as well as what makes it a complete end-to-end solution.
From data collection to dashboard visualization
“The first part of being able to do streaming data integration or analytics is that you need to be able to collect the data,” Wilkes said. The Striim platform has wizards to help build data flows and create streams SQL-based processing for filtering, transformation, aggregation, and enrichment of data, as well as a cache component to load reference data into memory.
Apache Kafka open-source stream processing software comes built into Striim, and target adapters allow write-out to cloud storage, such as Amazon Redshift or Azure Blob Storage. Ready to analyze the data?
“So you take the data stream, you build another data flow that is doing some aggregation of windows, maybe some complex event processing, and then use that dashboard builder to build a dashboard to visualize all of that,” Wilkes concluded.
Watch the complete video interview with Wilkes below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event.
