Christophe Blefari

FEBRUARY 23, 2024

My ideas these days ( credits ) Hey, fresh Data News edition. This week I've participated to a round table about data and did a cool presentation about Engines. The idea was to depict the history of engines over the last 40 years and what leads to polars and DuckDB. Obviously the I forgot a few things and I'll do a more complete v2 soon. This is my third presentation about DuckDB in the last 3 months and I think I'll slow down a bit until I get new crazy things to share.

Data Lake 130

Data Lake PostgreSQL MongoDB Scala 130

KDnuggets

FEBRUARY 23, 2024

It is a self-paced course that covers fundamental and advanced concepts of LLMs and teaches how to deploy them in production.

IT 123

IT 123

Monte Carlo

FEBRUARY 23, 2024

Over the past several years, data observability tooling has emerged as a must-have for every industry, from retail to security. And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. As generative AI (and the data powering it) takes center stage, it’s critical to bring this level of observability to where your data lives, in your data warehouse , data lake , or data lakehouse.

Systems 64

Systems Building Retail Data Lake 64

KDnuggets

FEBRUARY 23, 2024

KDnuggets' first Tech Brief is now available, and it outlines everything you need to know about MLOps.

IT 113

IT 113

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Business Intelligence

Precisely

FEBRUARY 23, 2024

Insurance is an inherently data-driven industry. Even before the age of advanced analytics, experts in the industry were routinely using data to assess risk and price policies. Today, data analytics plays a more important role than ever. Innovators are in a race to see who can use it to their best advantage. Insurance carriers have far more powerful tools at their disposal than in the past, enabling them to more accurately profile their customers, evaluate risk, and drive new business.

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Insurance Data Validation Government High Quality Data 64

KDnuggets

FEBRUARY 23, 2024

Every leader has their origin story, and here are some that might inspire you.

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127

Ascend.io

FEBRUARY 23, 2024

You are a data professional. This means that you are fully aware of the recent developments in AI and Large Language Models ( LLMs ). You’ve identified several complex challenges within your business that AI seems tailor-made to tackle. Exciting, isn’t it Yet, embarking on the AI adoption journey introduces a series of challenges, with one of the most significant being the readiness of your data platform.

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Monte Carlo

FEBRUARY 23, 2024

Over the past several years, data observability tooling has emerged as a must-have for every industry, from retail to security. And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. As generative AI (and the data powering it) takes center stage, it’s critical to bring this level of observability to where your data lives, in your data warehouse , data lake , or data lakehouse.

Systems 52

Systems Building Retail Data Lake 52

DataKitchen

FEBRUARY 23, 2024

DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps Data (and Analytic) Observability & Data Journey – Ideas and Background Data Journey Manifesto and Why the Data Journey Manifesto? Five Pillars of Data Journeys Data Journey First DataOps “You Complete Me,” said Data Lineage to Data Journeys. Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability The Need For Personalized Data Journeys for Your Data Consumers Data Te

Data Validation 47

Data Validation Data Data Pipeline Data Solutions 47