IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Data Warehouse 57

Data Warehouse Data Engineering Data Engineer Data Engineering 57

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

FEBRUARY 27, 2023

For today’s blog, we will be diving into the actual methods for implementing recommendation systems. Once we have a good understanding of those techniques, we will begin building a demo system by loading our training data into the Snowflake Data Cloud. How Do We Source Data to Train Recommendation Systems?

Database 52

Database Machine Learning Machine Learning Algorithm 52

Data Science Blog

MARCH 14, 2023

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre. In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt. Artificial Intelligence (AI) ersetzt.

Big Data 147

Big Data Big Data Apache Hadoop Hadoop 147

Data Science Blog

MARCH 30, 2023

Unabhängiges und Nachhaltiges Data Engineering Die Arbeit hinter Process Mining kann man sich wie einen Eisberg vorstellen. Diese AI ist in noch keiner Process Mining Software zu finden, kann jedoch bausteinartig dem Process Mining Data Warehouse vorgeschaltet werden. appeared first on Data Science Blog.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. An effective solution to this problem is the prediction of product categories. SageMaker is a fully managed ML service.

AWS 94

AWS ML ML Predictive Analytics 94