Lars Albertsson

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big data data engineering spark stream processing dataops data processing hadoop kafka #dataops #bigdata batch processing #dataengineering analytics privacy luigi data quality machine learning workflow orchestration software testing bigdata software development devsecops devops time data strategy data science agile #datastrategy #scala aviation safety risk management #shiftleft security supply chain lean #ethics #ai shiftleft covid-19 #lean data democratization data en openshift aws kubernetes ai gdpr organization project management testing cassandra scala event sourcing organising #functionalprogramming #softwarearchitecture #bigd recommendation systems count-min sketch spotify crunch

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About

Lars Albertsson

Presentations

Data Infrastructure for a World of Music

Scalable real-time processing techniques

Functional architectural patterns

Organising for Data Success

Data pipelines from zero

Data pipelines from zero to solid

Building real time data-driven products

Test strategies for data processing pipelines

A primer on building real time data-driven products

Testing data streaming applications

Protecting privacy in practice

10 ways to stumble with big data

Test strategies for data processing pipelines, v2.0

Privacy by design

Big data == lean data

Don't build a data science team

Kubernetes as data platform

Data ops in practice

Eventually, time will kill your data pipeline

Taming the reproducibility crisis

Eventually, time will kill your data processing

Engineering data quality

Data democratised

The lean principles of data ops

Data ops in practice - Swedish style

Mortal analytics - Covid-19 and the problem of data quality

The right side of speed - learning to shift left

Ai legal and ethics

DataOps - Lean principles and lean practices

Secure software supply chain on a shoestring budget

Likes

Culture over-process

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

The Mechanics of Testing Large Data Pipelines (QCon London 2016)

Comparison of various streaming technologies

Interactive Recommender Systems with Netflix and Spotify

10 more lessons learned from building Machine Learning systems