corpus.blog
41554 blogs · [ { "id": "01a087b8-d33e-737b-bfff-e4b44f27e7a1", "title": "Moving On", "url": "https://ondata.blog/uncategorized/moving-on/", "published_at": "2026-04-04T11:17:24+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b44f3bf705", "title": "Data Literacy: Six examples of bad data interpretation", "url": "https://ondata.blog/uncategorized/data-literacy-six-examples-of-bad-data-interpretation/", "published_at": "2024-04-29T14:40:23+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b45020c779", "title": "Porting PyTorch neural network to Amazon AWS", "url": "https://ondata.blog/articles/porting-pytorch-neural-network-to-amazon-aws/", "published_at": "2022-06-30T10:42:24+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b4507bbb3c", "title": "Porting pyTorch cloud detection model to Amazon AWS S3", "url": "https://ondata.blog/articles/porting-pytorch-image-recognition-model-to-amazon-aws-s3/", "published_at": "2022-06-17T20:03:47+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b4509caa75", "title": "pushing data to AWS. SageMaker sucks. So does Anaconda", "url": "https://ondata.blog/articles/aws-sagemaker-anaconda/", "published_at": "2022-06-14T17:41:18+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b4511442f2", "title": "Linear Regression: Killer App with 19-century maths", "url": "https://ondata.blog/articles/linear-regression-killer-app/", "published_at": "2022-01-19T17:57:17+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b4512e8a3c", "title": "Democratization of statistics: Chi2 for non-experts", "url": "https://ondata.blog/articles/democratization-of-statistics-chi2-for-non-experts/", "published_at": "2022-01-12T14:07:43+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b451c666e5", "title": "An approach to categorize multi-lingual phrases", "url": "https://ondata.blog/articles/categorize-multi-lingual-phrases/", "published_at": "2021-12-15T16:43:21+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b452bacf73", "title": "The implications of Scikit-learn bug #21455", "url": "https://ondata.blog/articles/implications-scikit-learn-21455/", "published_at": "2021-11-29T16:35:42+00:00" }, { "id": "01a087b8-d33e-737b-bfff-e4b452eb1c00", "title": "Your model may be inaccurate", "url": "https://ondata.blog/articles/your-model-may-be-inaccurate/", "published_at": "2021-11-25T12:27:51+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d682da810cc", "title": "Answering Why (with Chi-Square)", "url": "https://ondata.blog/articles/answering-why-chi-square/", "published_at": "2021-11-19T14:09:19+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d682e70ba53", "title": "What makes Data Quality so difficult", "url": "https://ondata.blog/articles/5-detective-stories-quality/", "published_at": "2021-11-08T15:12:41+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d682ee35a34", "title": "Don’t trust Data Science. Ask the people", "url": "https://ondata.blog/articles/dont-trust-data-science-ask-the-people/", "published_at": "2021-10-24T11:34:17+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d682ef55f46", "title": "Mistaken by factor of 100,000", "url": "https://ondata.blog/articles/mistaken-by-factor-of-100000/", "published_at": "2021-10-14T21:16:01+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d682fb22150", "title": "Practical AIOps: 5 use cases", "url": "https://ondata.blog/articles/aiops/", "published_at": "2021-06-08T18:52:26+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d6830299b27", "title": "How to delete your data for good", "url": "https://ondata.blog/articles/delete-data-for-good/", "published_at": "2021-06-01T21:35:13+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d6830bff3a2", "title": "I stopped writing reports, and so can you", "url": "https://ondata.blog/articles/i-stopped-writing-reports/", "published_at": "2021-04-21T23:15:52+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d68311d7287", "title": "Nine Circles of Hell: time in Python", "url": "https://ondata.blog/articles/nine-circles-of-hell-time-in-python/", "published_at": "2021-04-15T16:09:17+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d683170d5cb", "title": "Data Puzzle explained", "url": "https://ondata.blog/articles/data-puzzle-explained/", "published_at": "2021-03-29T22:42:16+00:00" }, { "id": "01a0bdc9-86af-71b0-b5ac-0d68318a987b", "title": "Data Puzzle", "url": "https://ondata.blog/articles/data-puzzle/", "published_at": "2021-03-24T14:36:19+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a3382175c3e5", "title": "A picture worth 1,000 words", "url": "https://ondata.blog/articles/a-picture-worth-1000-words/", "published_at": "2021-02-27T18:25:09+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33821d623f9", "title": "How to tell anomalies in data drift", "url": "https://ondata.blog/articles/how-to-tell-anomalies-in-data-drift/", "published_at": "2021-02-22T18:21:19+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a338227b6197", "title": "Kolmogorov-Smirnov test: a practical intro", "url": "https://ondata.blog/articles/kolmogorov-smirnov-test-a-practical-intro/", "published_at": "2020-10-30T13:56:32+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33823489672", "title": "Are people fair?", "url": "https://ondata.blog/articles/are-people-fair/", "published_at": "2020-10-23T14:36:25+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33823ce156e", "title": "The phantom I followed", "url": "https://ondata.blog/articles/the-phantom-i-followed/", "published_at": "2020-10-18T09:02:42+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33824beae24", "title": "When Accuracy Grows But Precision Falls", "url": "https://ondata.blog/articles/when-accuracy-grows-but-precision-falls/", "published_at": "2020-07-23T08:36:30+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33825014a9c", "title": "3 Steps to Unmask Data in Camouflage", "url": "https://ondata.blog/articles/unmask-data-camouflage/", "published_at": "2020-06-29T12:03:32+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33825ddc4c7", "title": "The truth behind a histogram dent", "url": "https://ondata.blog/articles/histogram-dent/", "published_at": "2020-06-19T07:27:29+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33826c475e4", "title": "No, the virus did NOT survive 17 days.", "url": "https://ondata.blog/articles/virus-didnot-survive-17-days/", "published_at": "2020-04-11T08:12:00+00:00" }, { "id": "01a0bdd1-0f8d-7087-a15f-a33826f3c9ef", "title": "How herd instinct hijacked herd immunity", "url": "https://ondata.blog/articles/how-herd-instinct-hijacked-herd-immunity/", "published_at": "2020-04-02T06:51:47+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53659e01cd", "title": "Coronavirus mortality: less than we think", "url": "https://ondata.blog/articles/coronavirus-mortality/", "published_at": "2020-03-29T13:06:13+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a5365ff038c", "title": "Data Lake: simple usage example", "url": "https://ondata.blog/articles/data-lake-simple-usage-example/", "published_at": "2020-03-26T12:34:29+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a5366ab022a", "title": "Techniques for comparing populations of IT data", "url": "https://ondata.blog/articles/simple-techniques-for-comparing-populations-of-it-data-events-incidents-support-tickets-and-alarms/", "published_at": "2020-03-02T23:09:44+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53673cb18e", "title": "The Data Lake at Sopra Steria", "url": "https://ondata.blog/articles/data-lake-at-sopra-steria-to-improve-analyst-effectiveness/", "published_at": "2020-02-17T13:59:12+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53682afd98", "title": "Synchronizing an SQL Database to a Data Lake (Change Data Capture at ingest)", "url": "https://ondata.blog/articles/ingesting-and-synchronizing-a-relational-database-to-a-data-lake/", "published_at": "2019-11-29T17:39:05+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53687507a9", "title": "Why Analysts need Data Lakes?", "url": "https://ondata.blog/articles/why-analysts-need-data-lakes/", "published_at": "2019-10-14T15:22:34+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53692b8c0b", "title": "Simple hack to improve data clustering visualizations", "url": "https://ondata.blog/articles/simple-ways-to-improve-data-clustering-visualizations/", "published_at": "2019-10-08T16:16:41+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a536947bf66", "title": "How to isolate data that constitutes a spike in histogram?", "url": "https://ondata.blog/articles/analysis-of-anomalies-in-histograms/", "published_at": "2019-10-01T13:50:38+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a53695750c4", "title": "Getting started: Apache Spark, PySpark and Jupyter in a Docker container", "url": "https://ondata.blog/articles/getting-started-apache-spark-pyspark-and-jupyter-in-a-docker-container/", "published_at": "2019-05-17T13:46:06+00:00" }, { "id": "01a0bdd4-df2d-721b-a8aa-2a5369c6720a", "title": "Building End-to-End Production Machine Learning pipelines", "url": "https://ondata.blog/articles/building-end-to-end-production-machine-learning-pipelines/", "published_at": "2019-04-21T07:32:54+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3a8cdda5", "title": "Audit logging for Amazon Redshift", "url": "https://ondata.blog/articles/audit-logging-for-amazon-aws-redshift/", "published_at": "2019-04-03T12:16:03+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3b8b8e35", "title": "Taking advantage of Machine Learning (ML), without even starting", "url": "https://ondata.blog/articles/taking-advantage-of-machine-learning-without-even-starting/", "published_at": "2019-03-21T14:44:20+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3c364d09", "title": "4 reasons for building Data Lakes… or not", "url": "https://ondata.blog/articles/4-reasons-for-building-data-lakes-or-not/", "published_at": "2019-03-15T14:47:30+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3cd5e069", "title": "Lecture notes: Introduction to Apache Spark", "url": "https://ondata.blog/articles/lecture-notes-introduction-to-apache-spark/", "published_at": "2019-03-14T13:57:20+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3cfc5b04", "title": "Product Owner vs Product Manager vs Architect", "url": "https://ondata.blog/articles/on-the-usage-of-terms-product-owner-software-architect-and-product-manager/", "published_at": "2019-03-13T11:56:21+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3d73924f", "title": "Collected thoughts on implementing Kafka data pipelines", "url": "https://ondata.blog/articles/collected-thoughts-on-implementing-kafka-data-pipelines/", "published_at": "2019-03-08T11:34:30+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3e189ec8", "title": "Introducing my Big Data orientation workshops", "url": "https://ondata.blog/articles/data-engineering-for-data-scientists-my-workshop-at-tophpc-conference/", "published_at": "2019-02-28T16:08:07+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3e264e76", "title": "Git version control: part 2", "url": "https://ondata.blog/articles/git-version-control-part-2/", "published_at": "2019-01-08T17:33:08+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3e26db2f", "title": "Data Engineering + Data Science: building the full stack", "url": "https://ondata.blog/articles/data-engineering-data-science-building-the-full-stack/", "published_at": "2019-01-05T00:26:17+00:00" }, { "id": "01a0bdd8-2003-707c-98ef-717b3ec1ba35", "title": "Git version control: concise introduction", "url": "https://ondata.blog/articles/concise-introduction-to-git-version-control/", "published_at": "2019-01-01T09:18:04+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20d6df994", "title": "Should justice use AI?", "url": "https://ondata.blog/articles/big-data-in-the-hands-of-government/", "published_at": "2018-12-16T03:28:53+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20dc05371", "title": "Lecture notes: an intro to Apache Spark programming", "url": "https://ondata.blog/articles/lecture-notes-an-intro-to-apache-spark-programming/", "published_at": "2018-12-13T14:33:21+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20e05408f", "title": "Top 10 Data Infrastructure technologies for a Data Scientist", "url": "https://ondata.blog/articles/how-much-a-data-scientist-should-know-about-the-infrastructure/", "published_at": "2018-12-06T16:07:50+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20e266504", "title": "Graph Databases: Cosmos DB Graph API – Key Concepts and Best Practices", "url": "https://ondata.blog/articles/graph-databases-in-big-data-key-concepts-and-best-practices-when-working-with-cosmos-dbs-graph-api/", "published_at": "2018-11-23T20:05:58+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20e4094df", "title": "Lecture Notes: Hadoop HDFS orientation", "url": "https://ondata.blog/articles/lecture-notes-how-hadoop-hdfs-works/", "published_at": "2018-11-21T01:18:18+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20ee3c9a9", "title": "Lecture notes: first steps in Hadoop", "url": "https://ondata.blog/articles/lecture-notes-setting-up-hadoop/", "published_at": "2018-11-21T00:46:09+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20ef50617", "title": "Installing Oracle Database on Windows 10", "url": "https://ondata.blog/articles/installing-oracle-database-on-windows-10/", "published_at": "2018-10-19T08:04:49+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20f8d0187", "title": "Data Engineering & Data Science in 30 hours", "url": "https://ondata.blog/articles/data-engineering-data-science-in-30-hours/", "published_at": "2018-09-03T08:32:59+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e20fe9cab5", "title": "Big Data in 30 hours and…. $250", "url": "https://ondata.blog/articles/big-data-in-30-hours-and-250/", "published_at": "2018-07-11T06:27:26+00:00" }, { "id": "01a0bddc-49aa-7349-9253-46e210990b95", "title": "To start this blog", "url": "https://ondata.blog/articles/my-second-post/", "published_at": "2016-11-18T07:13:21+00:00" } ] posts Claim your blog
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Blog · corpus.blog/blogs/ondata.blog/posts

ondata.blog

ondata.blog

2026

Moving Onoriginal ↗
4 Apr 2026

2024

Data Literacy: Six examples of bad data interpretationoriginal ↗
29 Apr 2024

2022

Porting PyTorch neural network to Amazon AWSoriginal ↗
30 Jun 2022
Porting pyTorch cloud detection model to Amazon AWS S3original ↗
17 Jun 2022
pushing data to AWS. SageMaker sucks. So does Anacondaoriginal ↗
14 Jun 2022
Linear Regression: Killer App with 19-century mathsoriginal ↗
19 Jan 2022
Democratization of statistics: Chi2 for non-expertsoriginal ↗
12 Jan 2022

2021

An approach to categorize multi-lingual phrasesoriginal ↗
15 Dec 2021
The implications of Scikit-learn bug #21455original ↗
29 Nov 2021
Your model may be inaccurateoriginal ↗
25 Nov 2021
Answering Why (with Chi-Square)original ↗
19 Nov 2021
What makes Data Quality so difficultoriginal ↗
8 Nov 2021
Don’t trust Data Science. Ask the peopleoriginal ↗
24 Oct 2021
Mistaken by factor of 100,000original ↗
14 Oct 2021
Practical AIOps: 5 use casesoriginal ↗
8 Jun 2021
How to delete your data for goodoriginal ↗
1 Jun 2021
I stopped writing reports, and so can youoriginal ↗
21 Apr 2021
Nine Circles of Hell: time in Pythonoriginal ↗
15 Apr 2021
Data Puzzle explainedoriginal ↗
29 Mar 2021
Data Puzzleoriginal ↗
24 Mar 2021
A picture worth 1,000 wordsoriginal ↗
27 Feb 2021
How to tell anomalies in data driftoriginal ↗
22 Feb 2021

2020

Kolmogorov-Smirnov test: a practical introoriginal ↗
30 Oct 2020
Are people fair?original ↗
23 Oct 2020
The phantom I followedoriginal ↗
18 Oct 2020
When Accuracy Grows But Precision Fallsoriginal ↗
23 Jul 2020
3 Steps to Unmask Data in Camouflageoriginal ↗
29 Jun 2020
The truth behind a histogram dentoriginal ↗
19 Jun 2020
No, the virus did NOT survive 17 days.original ↗
11 Apr 2020
How herd instinct hijacked herd immunityoriginal ↗
2 Apr 2020
Coronavirus mortality: less than we thinkoriginal ↗
29 Mar 2020
Data Lake: simple usage exampleoriginal ↗
26 Mar 2020
Techniques for comparing populations of IT dataoriginal ↗
2 Mar 2020
The Data Lake at Sopra Steriaoriginal ↗
17 Feb 2020

2019

Synchronizing an SQL Database to a Data Lake (Change Data Capture at ingest)original ↗
29 Nov 2019
Why Analysts need Data Lakes?original ↗
14 Oct 2019
Simple hack to improve data clustering visualizationsoriginal ↗
8 Oct 2019
How to isolate data that constitutes a spike in histogram?original ↗
1 Oct 2019
Getting started: Apache Spark, PySpark and Jupyter in a Docker containeroriginal ↗
17 May 2019
Building End-to-End Production Machine Learning pipelinesoriginal ↗
21 Apr 2019
Audit logging for Amazon Redshiftoriginal ↗
3 Apr 2019
Taking advantage of Machine Learning (ML), without even startingoriginal ↗
21 Mar 2019
4 reasons for building Data Lakes… or notoriginal ↗
15 Mar 2019
Lecture notes: Introduction to Apache Sparkoriginal ↗
14 Mar 2019
Product Owner vs Product Manager vs Architectoriginal ↗
13 Mar 2019
Collected thoughts on implementing Kafka data pipelinesoriginal ↗
8 Mar 2019
Introducing my Big Data orientation workshopsoriginal ↗
28 Feb 2019
Git version control: part 2original ↗
8 Jan 2019
Data Engineering + Data Science: building the full stackoriginal ↗
5 Jan 2019
Git version control: concise introductionoriginal ↗
1 Jan 2019

2018

Should justice use AI?original ↗
16 Dec 2018
Lecture notes: an intro to Apache Spark programmingoriginal ↗
13 Dec 2018
Top 10 Data Infrastructure technologies for a Data Scientistoriginal ↗
6 Dec 2018
Graph Databases: Cosmos DB Graph API – Key Concepts and Best Practicesoriginal ↗
23 Nov 2018
Lecture Notes: Hadoop HDFS orientationoriginal ↗
21 Nov 2018
Lecture notes: first steps in Hadooporiginal ↗
21 Nov 2018
Installing Oracle Database on Windows 10original ↗
19 Oct 2018
Data Engineering & Data Science in 30 hoursoriginal ↗
3 Sept 2018
Big Data in 30 hours and…. $250original ↗
11 Jul 2018

2016

To start this blogoriginal ↗
18 Nov 2016