Analytics

Machine Learning with Jupyter: Solving the Workflow Management Problem using Open-platforms

The infamous data science workflow with interconnected circles of data acquisition, wrangling, analysis, and reporting understates the multi-connectivity and non-linearity of these components. The same is true for machine learning and deep learning workflows. I understand the need for oversimplification is expedient in presentations and executive summaries. However, it may paint unrealistic pictures, hide the intricacies of ML development and conceal the realities of the mess.

Yellowfin 9.3 Release Highlights

Broadcasting is now available in this release for both dashboards and presentations. Just like reports, you can now enable scheduled delivery of these analytic content to different audiences. We have also included additional options for schedules — making it more granular for specific frequencies. For example, for fortnightly broadcasts I can now set the delivery to be on the second Monday. Or for monthly broadcasts, to have deliveries happen on the fifth day every month.

New Applied ML Research: Meta-Learning & Structural Time Series

At Cloudera Fast Forward we work to make the recently possible useful. Our goal is to take the incredible data science and machine learning research developments we see emerging from academia and large industrial labs, and bridge the gap to products and processes that are useful to practitioners working across industries.

Data security vs usability: you can have it all

Growing up, were you ever told you can’t have it all? That you can’t eat all the snacks in one sitting? That you can’t watch the complete Back to the Future trilogy as well as study for your science exam in one evening? Over time, we learn to set priorities, make a decision for one thing over the other, and compromise. Just like when it comes to data access in business.

MISRA Compliance:2020 and Other Panic Attacks

We are delighted to being invited again to Germany’s leading embedded software conference the ESE Kongress. We will be focusing on the MISRA language standard as commonly used in the automotive, avionics and wider safety critical space and educate about the importance of MISRA Compliance as defined in 2020. MISRA can be overwhelming for new projects and it is essential to understand the constraints as well as the freedoms regarding MISRA compliance.

Why We Need the Data Fabric

Computer science loves abstraction, and now, as it turns out, so does data management. Abstraction means reducing something complex to something simpler that elegantly delivers its essence. Applications all over the world become more robust and easier to maintain and evolve when a simple interface is put in front of a complex service. The consumer of the service is able to say: This is a lot simpler than allowing the consumer to reach directly under the hood and mess with the engine.