Big Data Conference Europe 2022
2022-11-23..2022-11-24
-- online --
[Big Data Conference Europe 2019, Big Data Conference Europe 2022, Big Data Conference Europe 2023, Big Data Conference Europe 2025]
| title | author | length |
|---|---|---|
| KEYNOTE: You Are Overthinking Data Quality | Steve Upton | 58m |
Argument: teams are overcomplicating data quality when specifics matter — what is the precise failure mode, what tests catch it, how many rows break it, and… | ||
| Keeping Your AI/ML Data Secure | Radu Vunvulea | 45m |
Claim: 80% of security breaches involve privileged credentials and roughly half of databases lack encryption; about 25% of organisations see cryptojacking… | ||
| PostgreSQL Distributed & Secure Database Ecosystem Building | Juan Pan | 42m |
Claim: transform existing PostgreSQL into a sharded, compute/storage–split database using Apache ShardingSphere, deploying stateless distributed SQL compute… | ||
| Encounters of the Third Kind With the Multimodal Generative AI Revolution | Javier Ideami | 43m |
Claims that generative models recreate humanlike system one creativity get concrete here: recent projects include dead Jennifer's and the Lost landscape… | ||
| Methods and Tools for Time Series Data Science Problems | Jay Alexander Clifford | 44m |
Shows a concrete pipeline: data ingested by Telegraf execd processor, fed to a Python script using statsmodels to apply Holt Winters (double/triple exponential… | ||
| Challenges and IBM Hardware Strategy to Cater With Clients Needs | Eric Aquaronne | 43m |
Claims that CPU P10/P11 and Z P11 chips embed AI accelerators to run inference at transaction time and cut latency into single-digit milliseconds for hundreds… | ||
| Foundations of Data Teams | Jesse Anderson | 39m |
Claims a 85% fail rate for data projects and argues failures come from missing specifics not wrong vendors; recommends staffing where a data scientist has 1:2… | ||
| Modernizing DataPlatform & Accelerating Business With Insights | Justina Sabiene, Josefine Boqvist | 46m |
Telia modernizes a cross‑market analytics stack that runs 3 million queries/day, serves ~5,000 active Click users and shares 100+ common analytical products… | ||
| Daniele Montesi & Emanuele Viglianisi | Daniele Montesi, Emanuele Viglianisi | 41m |
Scalable platform Zero2Hero runs on Azure and Databricks ingesting ~0.5 TB/day through Event Hubs into bronze/silver/gold Delta tables with ~200 ETL pipelines… | ||
| Practical Aspects of Applying Modern Computer Vision Technologies | Daria Lashkevich | 41m |
Built a factory Quality Inspector from cameras to deployment that runs 200+ use cases across nine plants, claims savings of €10k–€1M per year, and meets client… | ||
| Marija Selakovic | Marija Selakovic | 42m |
Claims that CrateDB handles industrial time series by combining SQL with Lucene-based indexing and columnar doc values for fast aggregations, using a… | ||
| Gender Bias in Artificial Intelligence | Shalvi Mahajan | 22m |
Claims: translation tools map doctor to male and nurse to female, credit-card automation gives identical-history women lower limits, facial recognition… | ||
| How to Detect Malware in Encrypted Traffic WITHOUT Decryption | Flo Pachinger | 51m |
Claims that metadata alone flags malware without decryption using TLS client hello fingerprints plus destination context and a weighted Naive Bayes classifier… | ||
| Panel Discussion: Business Side of Data Science | 46m | |
Panelists cite concrete claims and measures: 92 percent say culture not tech blocks adoption, surveys report one in four AI initiatives reach production but… | ||
| Data Horizons With Postgres | Bruce Momjian | 48m |
Argues that Postgres is a practical relational plus platform built for mixed workloads: native JSONB with GIN indexing, full‑text search via GIN/GIST, GIS via… | ||
| Machine Learning + Graph Databases for Better Recommendations | Christopher Woodward | 50m |
A demo movie site called Arango Flix demonstrates storing similarity edges in ArangoDB and serving recommendations via AQL; content methods use TF IDF and BM25… | ||
| Getting Started With Data Pipelines Using Apache Airflow | Ricardo Sueiras | 46m |
Shows a working Apache Airflow pipeline defined as Python DAGs, using bash, Python, S3 sensors, Athena and Redshift operators, run locally with a provided… | ||
| KEYNOTE: The Names of The Data Leadership Game | Pawel Rzeszucinski | 50m |
Argues data leadership is an infinite game and efficiency matters at three levels: individual, team, organization; claims 70% experience it (impostor syndrome)… | ||
| AI in a Minefield: Learning from Poisoned Data | Johnathan Azaria | 46m |
Clear, concrete coverage of how training-data attacks work and real examples — fake review campaigns, spam-label poisoning against Gmail, and steganographic… | ||
| One Year in a Data Mesh at PayPal | Jean-Georges Perrin | 49m |
Claims a homegrown data mesh at PayPal delivers faster, governed analytics by treating domain-aligned data quanta as products with built-in discovery and… | ||
| FLiP Into Pulsar Apps | Timothy J Spann | 46m |
Claims that Apache Pulsar unifies messaging and streaming with tiered storage and compute/storage separation, supports mqtt and rabbitmq protocols, and has a… | ||
| Julia, Python, R & Scala – A Comparison From Experience | Stephan Sahm | 46m |
Promises concrete comparisons: cites multi dispatch and claims Julia beats Java/Scala for numeric code, shows Spark/Scala as the industrial standard for batch… | ||
| KEYNOTE: How We Developing Data Services/Products in GitLab.com | Radovan Bacovic | 51m |
GitLab.com describes an almost-100%-open-source enterprise data platform that dogfoods its own product, handles 13+ million users with a 1,600+ fully remote… | ||
| Notebook To Production | Nir Barazida | 39m |
Claims a reproducible path from notebook to production using six principles: host code as Python modules, version everything (code data models experiments)… | ||
| Indexing Your Office Documents | David Pilato | 48m |
Demonstrates how Apache Tika powers the ingest-attachment plugin to extract text and metadata from base64 blobs sent to Elasticsearch, shows the cost of… | ||
| AI in Selection of Candidates | Bas van de Haterd | 45m |
Claims and concrete results matter: cognitive testing for air traffic controllers yields a 160% improvement in quality of hire while broadening the pool by a… | ||
| Implement a Serverless Data Analytics strategy | Roberto Freato | 52m |
Concrete outcome first: Azure storage Gen2 holds month of event files that are partitioned by type/year/month/day and 35 reports merged into single Parquet… | ||
| Martin Förtsch, Thomas Endres & Jonas Mayer | Martin Förtsch, Thomas Endres, Jonas Mayer | 49m |
Claim: an ironic system that automates trash‑posting and replies on social media by fine‑tuning language models and synthesizing many voices. Implementation… | ||
| Measuring Data FAIRness: Lessons From the NHS, ONS and IPCC | Adam Milward | 42m |
Claims concrete wins: a Metadata Works catalog built to an ISO triple 179-based schema, populated by a push that yields 450 datasets in three months versus 15… | ||
| Developing Intuition For AI As A Leader: Path To Data Literacy | Kuba Misiorny | 46m |
Claims that narrow AI mainly reduces prediction costs and will spawn new business sectors, with specifics: training machine learning models on historical data… | ||
| Storage Requirements and Options for Running Spark on Kubernetes | Rachit Arora | 46m |
Concrete choices decide whether Spark on Kubernetes works: use mtdir for local scratch (host SSD tied to pod lifecycle) for high IOPS, use PVCs/CSI or NFS for… | ||
| Because Having an AI Ethics Code Is Essential for Every Person Within a Company | Mauro Bennici | 42m |
Argues every employee needs a clear AI ethics code and gives concrete failures: Cambridge Analytica harvesting Facebook data, MidJourney–generated art causing… | ||
| Open Source Entity Resolution Using Zingg | Sonal Goyal | 36m |
Zingg is an open source entity resolution system that combines a learned blocking model with a pairwise classifier, graph clustering and active learning to… | ||
| Explainable Machine Learning Explained | Karol Przystalski | 45m |
Claims: convolutional models reach ~90% on image tasks but learn spurious cues (husky/wolf uses snow), and FDA needs explainability for MedTech. Tools shown… | ||
| Watermarks - Practical Tool for Any Streaming and Event Processing Application | Christian Tzolov | 43m |
Watermarks give a concrete way to close event‑time windows: sources emit a watermark (min of per‑input maxima), processors advance when watermark passes a… | ||
| Changing Realities - The Final Frontier for Machine Learning? | Tim Frey | 39m |
Claim: real-world concept drift breaks static models and demands either continuous online learning or engineered features. Built an occupancy predictor for… | ||
| Esther Huyer & Raymonde Weyzen | Esther Huyer, Raymonde Weyzen | 46m |
Support Centre for Data Sharing documents concrete wins and tools: an API friendliness checker, modular model contracts and a certification scheme under the… | ||
| Legal Approach to the European Data Strategy | Rubén Cano | 47m |
European regulators map concrete barriers: concentrated silos, poor interoperability, low data quality, weak cyber incentives and missing skills; GDPR is only… | ||
| Multidimensional Indexing and Sampling on the Lake | Paola Pardo | 38m |
A multi‑dimensional index (Cubist / Qbeast format) stores one file per spatial cube with per‑file weights so queries can read only matching files, run sampling… | ||
| Shorten the Path to Production with In-Database Machine Learning | Paige Roberts | 46m |
Claims are concrete: Nimble Storage builds Infosight with in-database ML and HPE acquires it after 3× engineer productivity and 86% of cases auto-resolved… | ||
| KEYNOTE: Why Customers Can’t or Won’t Use Your Technically-Right Data Products | Brian O'Neill | 01h 05m |
Claim: technically sound analytics fail when outputs don’t map to human goals. Evidence: surveys show >80% adoption problems; a cathedral fire detection UI… | ||
| Panel Discussion: What is Hot in Data World in 2022? | 46m | |
Panelists describe concrete shifts not vague themes: Stable Diffusion open‑source release makes image models downloadable and sparks thousands of apps; large… | ||
| Increasing Data Awareness with Self-Serve Analytics | Shadi Rostami | 34m |
Describes concrete, actionable outcomes: amplitude adoption climbs from ~200 to 927 monthly users at one company and to 566 at another; a two‑month POC reaches… | ||
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