Blockchain, Integration, Streaming Analytics, Ethereum, Hyperledger
Kai Waehner
Blockchain, Integration, Streaming Analytics, Ethereum, Hyperledger => Why blockchain is the next big thing for middleware and analytics.
Browsing Category
Analytics
49 posts
Comparison: Data Preparation vs. Inline Data Wrangling in Machine Learning and Deep Learning Projects
Data Preparation: Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling in Machine Learning / Deep Learning Projects.
Streaming Analytics Comparison of Open Source Frameworks, Products, Cloud Services
Streaming Analytics Comparison of Open Source Frameworks, Products and Cloud Services. Includes Apache Storm, Flink, Spark, TIBCO, IBM, AWS Kinesis, Striim, Zoomdata, …
Machine Learning Applied to Microservices
Build intelligent Microservices by applying Machine Learning and Advanced Analytics. Leverage Apache Hadoop / Spark with Visual Analytics and Stream Processing.
Comparison Of Log Analytics for Distributed Microservices – Open Source Frameworks, SaaS and Enterprise Products
Log Analytics is the right framework or tool to monitor for Distributed Microservices. Comparison of Open source, SaaS and Enteprrise Products. Plus relation to big data components such as Apache Hadoop / Spark.
Characteristics of a Good Visual Analytics and Data Discovery Tool
Several tools are available on the market for Visual Analytics and Data Discovery. Three of the most well known options are Tableau, Qlik and TIBCO Spotfire. This post shows important characteristics to compare and evaluate these tools.
Streaming Analytics with Analytic Models (R, Spark MLlib, H20, PMML)
Closed Big Data Loop: 1) Finding Insights with R, H20, Apache Spark MLlib, PMML and TIBCO Spotfire. 2) Putting Analytic Models into Action via Event Processing and Streaming Analytics.
Framework and Product Comparison for Big Data Log Analytics and ITOA
Slide deck from OOP 2016: Comparison of Frameworks and Products for Big Data Log Analytics and ITOA, e.g. Open Source ELK, TIBCO LogLogic / Unity, Splunk, Papertrail; Relation to Hadoop is also discussed.
Comparison of Stream Processing Frameworks and Products
See how stream processing / streaming analytics frameworks (e.g. Apache Spark, Apache Flink, Amazon Kinesis) and products (e.g. TIBCO StreamBase, Software AG’s Apama, IBM InfoSphere Streams) are categorized and compared. Besides, understand how stream processing is related to Big Data platforms such as Apache Hadoop and machine learning (e.g. R, SAS, MATLAB).
Difference between a Data Warehouse and a Live Datamart?
Data Warehouses have existed for many years in almost every company. While they are still as good and relevant for the same use cases as they were 20 years ago, they cannot solve new, existing challenges and those sure to come in a ever-changing digital world. The upcoming sections will clarify when to still use a Data Warehouse and when to use a modern Live Datamart instead.
