John Santaferraro

It was all the way back in 2019 that I first published some research on the use of #AI and #ML in #data and #analytics. The data and analytics software vendors that were identified as leaders in the use of AI five years ago, continue to be the leaders in the use of generative AI today. Read the Ferraro Consulting POV paper on the five foundational software design principles that define leadership for the use of #genAI in today's convoluted market. What a privilege to be able to author this… Visualizza altro

It was all the way back in 2019 that I first published some research on the use of #AI and #ML in #data and #analytics. The data and analytics software vendors that were identified as leaders in the use of AI five years ago, continue to be the leaders in the use of generative AI today. Read the Ferraro Consulting POV paper on the five foundational software design principles that define leadership for the use of #genAI in today's convoluted market. What a privilege to be able to author this piece with Amit Soni. Amit is one of the brightest minds in the use of AI and ML, specifically in the #businessintelligence space. Ask him about the BI product that he designed with an interface just like the Google search page. It was brilliant. Meno dettagli

Congratulations to Steve Lucas and Boomi on their move from the lower left of the Gartner MQ for iPaaS to the upper right. What a great accomplishment. I've spent some time over the last month pondering how this might have happened. You can read my analysis and in the Ferraro Consulting POV paper, "Boomi's Journey: From Steadfast Leader to Innovator Extraordinaire." Let me give you some hints: hashtag#acquisition hashtag#integration hashtag#metadata hashtag#AI hashtag#culture… Visualizza altro

Congratulations to Steve Lucas and Boomi on their move from the lower left of the Gartner MQ for iPaaS to the upper right. What a great accomplishment. I've spent some time over the last month pondering how this might have happened. You can read my analysis and in the Ferraro Consulting POV paper, "Boomi's Journey: From Steadfast Leader to Innovator Extraordinaire." Let me give you some hints: hashtag#acquisition hashtag#integration hashtag#metadata hashtag#AI hashtag#culture hashtag#cultureshift hashtag#innovation hashtag#genAI hashtag#generativeAI hashtag#generalAI

Favorite quote from the paper: "The expanded offering with Unifi, a common rich set of metadata, and a central AI engine gave Boomi everything they needed to take full advantage of the 2023 generative AI boom and emerge as a leader of leaders in 2024." Meno dettagli

The keynote content and delivery at Kafka Summit London 2024 was some of the best I have seen in a long, long time. More importantly, the Confluent announcements have set them up for significant growth in the near future. The general availability of #Apache #Flink under the cover of Confluent's enterprise-grade cloud offering gives customers a single unified platform for both #datastreaming and #streamprocessing. They upped the ante by announcing up coming inclusion of #Iceberg in the same… Visualizza altro

The keynote content and delivery at Kafka Summit London 2024 was some of the best I have seen in a long, long time. More importantly, the Confluent announcements have set them up for significant growth in the near future. The general availability of #Apache #Flink under the cover of Confluent's enterprise-grade cloud offering gives customers a single unified platform for both #datastreaming and #streamprocessing. They upped the ante by announcing up coming inclusion of #Iceberg in the same platform, creating an #OpenSource trifecta. To connect operational and analytical domains, Confluent also released an early version of Tableflow, a transformer that takes data from Kafka, turns it on its side, and creates an Iceberg table. Meno dettagli

2024 will be the year that data integration dies. It will be swept away by new waves of more generic data engineering platforms designed to finally unify all use cases in a single platform.

Most enterprises have 6-8 different data integration and transformation platforms. Everyone is tired of having to integrate their integration efforts. They are done moving data in and out of separate data engineering environments to build their pipelines. The cost and complexity of continuing to… Visualizza altro

2024 will be the year that data integration dies. It will be swept away by new waves of more generic data engineering platforms designed to finally unify all use cases in a single platform.

Most enterprises have 6-8 different data integration and transformation platforms. Everyone is tired of having to integrate their integration efforts. They are done moving data in and out of separate data engineering environments to build their pipelines. The cost and complexity of continuing to operate in silos is not sustainable.

Even for companies just entering the data integration or data engineering space with only one or two use cases, it is vital to consider the trend toward unification. Why? One successful use case breeds two new cases; two new use cases can breed a dozen new opportunities. In the digital world, the need to move, transform, analyze, deliver, and automate insight will continue to accelerate, possibly without end.

John Santaferraro, CEO and Head Research Analyst at Ferraro Consulting, recently published a point of view paper highlighting the urgency for unified data engineering and defining this new category for prospective buyers. The paper, Unified Data Engineering: Consolidating Engineering Functions to Harness Artificial Intelligence, also includes a brief list of vendors in the race for unification. Meno dettagli

Deploying and managing Apache Kafka® for enterprise use cases is fraught with difficulty.

Challenges Running Kafka

Kafka is a distributed system, and like most distributed systems, operating it requires careful consideration of networking, resource allocation, faults, and recovery. While it is relatively easy to get started in using Kafka, building a reliable and trustworthy Kafka service can take many weeks or even months.

Yet today’s organizations are highly motivated to… Visualizza altro

Deploying and managing Apache Kafka® for enterprise use cases is fraught with difficulty.

Challenges Running Kafka

Kafka is a distributed system, and like most distributed systems, operating it requires careful consideration of networking, resource allocation, faults, and recovery. While it is relatively easy to get started in using Kafka, building a reliable and trustworthy Kafka service can take many weeks or even months.

Yet today’s organizations are highly motivated to overcome these challenges because the real-time insights and responsiveness Kafka can deliver offer powerful technical and business benefits. And although there are more than 1,000 use cases to date, the underlying reasons why Kafka projects fail are much more universal—which means their solutions are as well.

In this ebook, learn top six reasons why most Kafka projects fail:

Why Kafka operations are so resource-intensive
The demand for better security and governance capabilities
Challenges faced when planning and executing Kafka projects
The manual interventions and considerations needed when scaling Kafka
Read the ebook to learn about each of these challenges in detail, as well as how to overcome them with Confluent. Meno dettagli

Predictive data intelligence is the use of data, AI-driven algorithms, and machine learning techniques to quickly connect data consumers with the most relevant data they need to drive their business initiatives and deliver greater value.

The goal of predictive analytics is to go beyond simply describing data to enable data consumers to accelerate the next-best actions to take for more effective decision making. For example, a retailer can understand their most relevant and high-quality… Visualizza altro

Predictive data intelligence is the use of data, AI-driven algorithms, and machine learning techniques to quickly connect data consumers with the most relevant data they need to drive their business initiatives and deliver greater value.

The goal of predictive analytics is to go beyond simply describing data to enable data consumers to accelerate the next-best actions to take for more effective decision making. For example, a retailer can understand their most relevant and high-quality data sets to better forecast consumer demand for a product, or a financial institution may identify the most accurate, complete customer data used to fuel analytics that help identify the likelihood of default on a loan.

In this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Informatica’s Ian Stahl, Senior Director of Product Management and Chris Phillips, VP of Product Management to discuss:

*Shifting from business intelligence to predictive data intelligence
*Data sharing and data marketplaces
*The data consumption revolution Meno dettagli

Time is the new gold standard for big data success. John Santaferraro, Vice President of Solutions & Product Marketing at Actian joins John Furrier and Dave Vellante in theCUBE, discussing the importance of rapid innovation. The co-hosts also explore the progression from Big Data 1.0 to 2.0.

How can enterprises cost-effectively prepare for their data-driven future in the face of this shortage? The solution is an internal program that provides the opportunity for existing data analysts, BI analysts, and business analysts to acquire the skills they need to become big data analysts. These big data analysts then perform the predictive and prescriptive analysis and discovery needed to innovate and compete effectively.

Some organizations might be surviving the current economic hard times in part because they know how to use data better than their failing competitors. Can they extend their lead in good times with new cloud-aware analytics?

Companies that want to succeed in data analysis need the ability to combine analytic results in a simple, quick, and dynamic way.