In defense of the pie chart
Common mistakes that thwart a simple data visualization technique.
Big Data Tools and Pipelines
Ideas and resources related to data tools.
Embeddable data transformation for real-time streams
Moving data transformation into the hands of administrators, analysts, and other non-developers.
Best practices for data lakes
How to build, maintain, and derive value from your Hadoop data lake.
Why your next analytics project should be in procurement
Exploring the intersections and compatibility of data science and procurement.
BayesDB: Data science is a communication problem
Query languages, like BQL, offer a bridge between domain experts and software experts.
Get started with SQL: Plan and design a database
Dive into creating your own databases and learn how to design them efficiently.
Architecting Druid for failure
Guaranteeing data availability in distributed systems.
Lego-powered Kafka training
Jesse Anderson walks viewers through the path data can take from publishers through a Kafka cluster and on to consumers.
Multitenancy on Hadoop: Is your cluster half full?
Over-allocated but underutilized clusters require more than best practice solutions.
Deploying a hybrid Hadoop architecture
Metadata, governance, and other considerations for building ground-to-cloud.
Apache Cassandra for analytics: A performance and storage analysis
Comparing the effects of storage format, modeling/filtering, caching, and other effects on analytical query speed and storage cost.
NoSQL technologies are built to solve business problems, not just “wrangle big data”
Knowing the architectures is key to thinking strategically and delivering value.
Clustering geolocated data using Spark and DBSCAN
How to group users’ events using machine learning and distributed computing
Lessons on Hadoop application architectures
Choosing the right tools for the job.
Best kept machine learning secret in security
Ranking algorithms bolster intrusion detection systems.
Stop making excuses and get your data distributed
Globalize your data with Apache Cassandra.
“Managed data lake” is not a contradiction in terms
Data management is an important step in deriving business value from your Hadoop data lake.
Analytics without actions – why bother?
Streaming analytics are only worthwhile if the data leads to action.
Data modeling constructs and terminology
Identification of data sources is the first step in warehouse development. In this video training segment, Michael Blaha provides a framework by reviewing data modeling constructs and terminology, including dependent and independent entity types. Using IE (information engineering) notation and the ERwin tool, Blaha walks through a sample operational data model.
What happens when everyone can connect the dots
Everyone loves data, so it's no surprise that we've been innovating by orders of magnitude in data storage. But has analytics innovation kept up?
Analyzing the world’s news: Exploring the GDELT Project through Google BigQuery
What it looks like to analyze, visualize, and even forecast human society using global news coverage.
Ask your data new questions
Consolidating data across silos improves business insight.
Accelerating big data analytics workloads with Tachyon
How Baidu combined Tachyon with Spark SQL to increase speed 30-fold
Architecting Hadoop Applications
In this O'Reilly training video, the "Hadoop Application Architectures" authors present an end-to-end case study of a clickstream analytics engine to provide a concrete example of how to architect and implement a complete solution with Hadoop. In this segment, they provide an overview of the complete architecture. Presenters: Mark Grover, Gwen Shapira, Jonathan Seidman, Ted Malaska