Posts published in “DataOps”

Cloud Analytics: Utilizing Composable to turn your organization into a Data-Driven Company

Published September 16, 2016 by Andy Vidan

Cloud Analytics: Utilizing Composable to turn your organization into a Data-Driven Company

Major transformations are shaping the global economy, and it is now clear that organizations with the resources and know-how to leverage the large volume of both internal and external data…

Hadoop is Dead. DataFlow is Alive!

Published September 27, 2014 by Lars Fiedler

Hadoop is Dead. DataFlow is Alive!

We’ve given Hadoop almost 10 years to mature, invested billions, and very few companies are seeing the return on investment. Several companies have tried to make Hadoop a real-time analytical…

Leverage existing Hadoop cluster with CA

Published August 10, 2014 by Lars Fiedler

Leverage existing Hadoop cluster with CA

With the Hive ODBC driver and Composable Analytics, users can perform ad-hoc queries on their data living in the HDFS. Hive will take a sql-like query and translate it into…

Want to analyze Twitter data?

Published August 10, 2014 by Lars Fiedler

Want to analyze Twitter data?

Twitter analysis typically starts with grabbing a bunch of tweets via Twitter’s REST API. Fortunately this is easy to do with Composable Analytics. Just use the Twitter Search module, and…

Monash University: Research Fellow – Optimisation [Melbourne, Australia]
Seeking an enthusiastic researcher with solid skills in any of the following areas: constraint programming, mixed integer programming, SAT and SAT modulo theories, modelling languages and program analysis, to join an established team working on new approaches to modelling and solving discrete optimisation problems.
Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision
Dr. Takeo Kanade shared his life lessons from an illustrious 50-year career in Computer Vision at last year's Embedded Vision Summit. You have a chance to attend the 2019 Embedded Vision Summit, from May 20-23, in the Santa Clara Convention Center, Santa Clara CA.
60+ useful graph visualization libraries
We outline 60+ graph visualization libraries that allow users to build applications to display and interact with network representations of data.
PyCharm for Data Scientists
This article is a discussion of some of PyCharm's features, and a comparison with Spyder, an another popular IDE for Python. Read on to find the benefits and drawbacks of PyCharm, and an outline of when to prefer it to Spyder and vice versa.
7 Steps to Mastering SQL for Data Science — 2019 Edition
Follow these updated 7 steps to go from SQL data science newbie to practitioner in a hurry. We consider only the necessary concepts and skills, and provide quality resources for each.
A complete guide to K-means clustering algorithm
Clustering - including K-means clustering - is an unsupervised learning technique used for data classification. We provide several examples to help further explain how it works.
Why Data Professionals Should Negotiate Every Job Offer
Here are six reasons why you shouldn't feel tempted to jump at the chance and take that job offer as it is without first negotiating.
Large-Scale Evolution of Image Classifiers
Deep neural networks excel in many difficult tasks, given large amounts of training data and enough processing power. The neural network architecture is an important factor in achieving a highly accurate model... Techniques to automatically discover these neural network architectures are, therefore, very much desirable.
Top KDnuggets tweets, May 08-14: The end of average Data Scientist is near: @GoogleAI fully automated, End-to-End #AutoML #MachineLearning
Also: My favorite free courses to learn data structures and #algorithms in depth; “Please, explain.” Interpretability of machine learning models; Decoding ‘A Game of Thrones’ #GOT with data science; Another 10 Free Must-See Courses for Machine Learning and Data Science; Best Data Visualization Techniques for small and large data
Building Recommender systems with Azure Machine Learning service
Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure Machine Learning services.