Data in Motion Resources
Data-in-motion (DiM) refers to all real-time data that is continuously streamed into the enterprise from various data sources such as log streams, social streams, telemetry data, IoT devices, sensor data, and so on. Unlike traditional data-at-rest found in various data stores within the enterprise, data-in-motion carries the unique attribute of “data freshness” that is extremely valuable to any enterprise.
Resources
Introducing the Data-in-Motion Ecosystem Map
The Data-in-Motion Ecosystem Map shows the various moving parts of your data architecture and how they are all connected with each other.
Smart Talk Episode 7: Cardinality, Control and Costs in Observability
Cardinality, control, and costs are the three Cs of understanding and managing observability data as Krishna Yadappanavar, CEO of Kloudfuse explains with Smart Talk’s host, Dinesh Chandrasekhar, founder and principal...
Smart Talk Episode 6: AIOps and the Future of IT Monitoring
Observability tools watch millions of real-time data points. Thanks to AIOps these can be turned into actionable information or real-time automation.
Smart Talk Episode 5: Disaggregation of the Observability Stack
Observability adoption is growing fast–and the tech stacks running observability are becoming bloated. Watch our experts talk about why and what to do about it.
Smart Talk Episode 4: Real-Time Data and Vector Databases
General-purpose databases are changing to adapt to the new AI and GenAI workloads. Take Postgres which recently gained vector database extensions.
Smart Talk Episode 3: Modern Data Pipelines and LLMs
GenAI will help organizations to finally harness their unstructured data if they redesign their data pipelines with different transformations and built-in governance.
Smart Talk Episode 2: The Rise of GenAI Applications with Data-in-Motion
Discover the role data-in-motion plays in enterprise GenAI and how to augment LLMs trained on historical data with fresh or even real-time data.
Smart Talk Episode 1: The Data-in-Motion Ecosystem Landscape
Watch Manish, Product Executive, and Dinesh, Industry Analyst, talk about how enterprises create value from their data-in-motion by using the power of fresh, real-time data.
What Exactly is a Unified Real-time Platform
URPs are motivated by escalating business demands for smarter operational applications that can leverage up-to-the-second data to make faster and better decisions. Learn more about them here.
Unified Real-Time Platforms
Unified Real-Time Platforms (URPs) are a new category of software designed to handle demanding applications that deal with both streaming data and data at rest. They combine elements of traditional...
Four Kinds of Software to Process Streaming Data in Real Time
A look at the four kinds of software that perform real-time analytics on event streams and when to use each.
How to Select a Streaming Platform: A Practical Guide
With stream processing flipping the data processing paradigm from store then process to process then store, the critical capabilities to evaluate when building streaming applications are vastly different from those...
Beyond Kafka: Capturing the Data-in-motion Industry Pulse
To fully participate in today’s data-in-motion world requires that a data streaming platform be part of every company’s architecture.
Do You Need to Process Data “In Motion” to Operate in Real Time?
Quick answer: No, you don’t always need data in motion to operate in real time. However, some high volume/low latency real-time systems do use data in motion in the sense...
Contributors
Dinesh Chandrasekhar
Founder and principal, Stratola LLC
Dinesh Chandrasekhar is a seasoned marketing executive, a technology evangelist, and a thought leader with close to 30 years of industry experience.
Les Yeamans
Founder and Executive Editor of RTInsights and CDInsights
He is a business entrepreneur with over 25 years of experience developing and managing successful companies in the enterprise software, financial services, strategic consulting and Internet publishing markets
Roy Schulte
A former Gartner Fellow and co-author of the book “Event Processing: Designing IT Systems for Agile Companies”. He holds a BS and MS from MIT, and his recent work focuses...
Sumit Pal
An Ex Gartner-VP Analyst in Data Management & Analytics where he advised CTOs, CDOs, CDAOs, Enterprise Architects and Data Architects on Data Strategy, Data Architectures, implementation and choosing tools, frameworks,...
Sanjeev Mohan
Sanjeev Mohan is an established thought leader in the areas of cloud, modern data architectures, analytics, and AI. He researches and advises on changing trends and technologies and is the...
Manish Devgan
Product Executive
Manish Devgan, a product executive with a proven track record of delivering industry-leading software. He has successfully led the development of numerous products at companies such as BEA Systems, Oracle,...