dataflow analytics blog – Data Orchestration, Automation and Analytics

Error Handling Options in Composable

Published May 10, 2019 by Eric Lew

Composable strives to replicate the concepts of coding via a UI, and to further that goal, we added feature that allow the user to react to errors. There are three…

Welcome to Composable 2.0

Published January 2, 2019 by Ryan O'Shea

Welcome to Composable 2.0

As we dive into 2019, we’d like to tell you about one of the Composable team’s proudest accomplishments from the last year — the launch of Composable Enterprise 2.0. In…

Progress Metrics for DataFlows

Published January 2, 2019 by Mark Sherer

Composable has recently added progress-tracking features, including progress metrics and animations. Both of these aim to elucidated DataFlow execution by showing the modules that are currently executing and highlighting potential…

Code Reuse and Modularity in Composable

Published January 2, 2019 by Lars Fiedler

Composable provides special mechanisms for managing complexity of dataflows. Specifically, Composable allows you to reuse parts of your dataflow by encapsulating them as stand-alone custom modules. When developing your dataflow…

DataOps: Straightforward Data Migration

Published December 31, 2018 by Lars Fiedler

Business use cases sometimes demand the orchestration or migration of data from one Relational Database Management System (RDBMS) to another. For example, moving data from MySQL to Oracle, or from…

WIX: Scheduling a custom database upgrade to happen After=”InstallSqlData” and Before=”StartServices”

Published October 24, 2018 by Lars Fiedler

At Composable, we develop MSIs for deploying and upgrading instances of the Composable platform. Anytime we want to update an instance, we just simply double click on the latest Composable…

Correcting Pesky Timezones in a DataFlow

Published June 21, 2018 by Ryan O'Shea

Anyone who works with lots of data can attest that dealing with time and timezones can be tricky business. At Composable, we orchestrate millions of pieces of date/time data through…

KDnuggets

First hand experience from Uber, Microsoft, Delivery Hero & more – at PAW London

Top practitioners are coming to PAW London, 16-17 Oct 2019, to describe the design, deployment and business impact of their machine learning projects. Register using code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket.

McKinsey: Data Engineer [Wroclaw, Poland]

McKinsey is seeking a Data Engineer in Wroclaw, Poland, to enable effective, highly scalable data analysis pipelines and play a critical role in database design, development, data integration and ingestion, as well as designing ETL architectures using a variety of ETL tools and techniques.

McKinsey: Data Scientist [Wroclaw, Poland]

McKinsey is seeking a Data Scientist in Wroclaw, Poland, to work with McKinsey clients and consulting teams to carry out complex data analysis and modeling, creating a foundation for sound recommendations for client studies and internal projects.

Scaling a Massive State-of-the-art Deep Learning Model in Production

A new NLP text writing app based on OpenAI's GPT-2 aims to write with you -- whenever you ask. Find out how the developers setup and deployed their model into production from an engineer working on the team.

Secrets to a Successful Data Science Interview

Are you puzzled as to what to prepare for data science interviews? That you are reading this document is a reflection of your seriousness in being a successful data scientist.

The Hackathon Guide for Aspiring Data Scientists

This article is an overview of how to prepare for a hackathon as an aspiring data scientist, highlighting the 4 reasons why you should take part in one, along with a series of tips for participation.

Also: What's wrong with the approach to Data Science?; Introducing Gen: MITs New Language That Wants to be the TensorFlow of Programmable Inference; Top 10 Data Science Leaders You Should Follow; 5 Probability Distributions Every Data Scientist Should Know; XGBoost and Random Forest with Bayesian Optimisation

Introducing Gen: MIT’s New Language That Wants to be the TensorFlow of Programmable Inference

Researchers from MIT recently unveiled a new probabilistic programming language named Gen, a language which allow researchers to write models and algorithms from multiple fields where AI techniques are applied without having to deal with equations or manually write high-performance code.

Pre-training, Transformers, and Bi-directionality

Bidirectional Encoder Representations from Transformers BERT (Devlin et al., 2018) is a language representation model that combines the power of pre-training with the bi-directionality of the Transformer’s encoder (Vaswani et al., 2017). BERT improves the state-of-the-art performance on a wide array of downstream NLP tasks with minimal additional task-specific training.

Top June Stories: 5 Useful Statistics Data Scientists Need to Know; 7 Steps to Mastering Intermediate Machine Learning with Python – 2019 Edition

Also: Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS; If you're a developer transitioning into data science, here are your best resources.