Iterative data modeling to avoid dreaded ETL
Gain agility by loading first and transforming later.
Data
Our take on the ideas, information, and tools that make data work.
Re-thinking marketing: Generating attention you can turn into profitable demand
The media and ad tech sessions at the Strata Data Conference in San Jose will dig deep into how media businesses are changing.
Different continents, different data science
Regardless of country or culture, any solid data science plan needs to address veracity, storage, analysis, and use.
“Data as a feature” is coming. Are product managers ready?
By packaging and delivering actionable data in applications, product managers can help users achieve their goals.
Enterprise data integration with an operational data hub
Facilitating data exchange across the enterprise.
Apache Beam lowers barriers to entry for big data processing technologies
The classic “write once, run everywhere” principle comes to life in streaming data.
Fishing for graphs in a Hadoop data lake
Exploring many small regions of a graph with low latency using specialized graph and multi-model databases.
Put machine learning to work in the real world
The sessions and training courses at Strata Data San Jose 2018 will focus on practical use cases of machine learning for data scientists, engineers, managers, and executives.
Square off: Machine learning libraries
Top five characteristics to consider when deciding which library to use.
An introduction to regular expressions
Decoding simple regex features to match complex text patterns.
How enterprises can build a digital business platform with pervasive integration
Every line of business must have access to the digital tools needed to innovate at the edge.
Stop the fights. Embrace data
Felipe Hoffa says data-based conclusions are possible when stakeholders can easily analyze all relevant data.
Associative memory AI aids in the battle against financial crime
The O’Reilly Media Podcast: Gayle Sheppard, Saffron AI Group at Intel, and David Thomas, Bank of New Zealand.
Rethinking data marts in the cloud
Become more agile with business intelligence and data analytics.
Emotional arithmetic: How machine learning helps you understand customers in real time
Chad W. Jennings walks through a serverless big data architecture on Google Cloud that helps unravel the mysteries of human emotion.
Will AI help save the snow leopard?
Joseph Sirosh shares a story about a volunteer’s dilemma, an engineer’s ingenuity, and how AI, cloud, data, and devices came together to save snow leopards.
Analytics everywhere, from things to cities
There are endless possibilities when we connect the unconnected. Raghunath Nambiar discusses the magnitude of challenges and opportunities across industry segments.
Teaching databases to learn in the world of AI
Nikita Shamgunov explores the future of databases for fast-learning adaptable applications.
A whole new way to think about your next gen applications
Anil Gadre shares how MapR customers using a converged data platform are creating new apps for the enterprise.
Unleashing intelligence and data analytics at scale
Ziya Ma explains how Intel is driving a holistic approach to powering advanced analytics and artificial intelligence workloads.
Data liquidity in the age of inference
Probabilistic computation holds too much promise for it to be stifled by playing zero sum games with data.
What are the challenges in building an anomaly detection system?
Learn about some of the common issues you will encounter when developing algorithms for a modern anomaly detection system.
Why might an off-the-shelf anomaly detection technique not work in practice?
See examples of the many traps you can fall into if you use off-the-shelf anomaly detection techniques.
What are the challenges in building an anomaly detection system for streaming and live data?
Learn the difference between live and streaming anomaly detection systems and how to address the challenges different data velocities pose.