Remove Data Engineering Remove Data Lakes Remove Predictive Analytics
article thumbnail

Data lakehouse

Dataconomy

Data Lakehouse has emerged as a significant innovation in data management architecture, bridging the advantages of both data lakes and data warehouses. By enabling organizations to efficiently store various data types and perform analytics, it addresses many challenges faced in traditional data ecosystems.

article thumbnail

AWS re:Invent 2023 Amazon Redshift Sessions Recap

Flipboard

Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches.

AWS 135
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

40 Must-Know Data Science Skills and Frameworks for 2023

ODSC - Open Data Science

Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed. This pushes into big data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

Data scientists will typically perform data analytics when collecting, cleaning and evaluating data. By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. Watsonx comprises of three powerful components: the watsonx.ai

article thumbnail

Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

AWS Machine Learning Blog

With over 50 connectors, an intuitive Chat for data prep interface, and petabyte support, SageMaker Canvas provides a scalable, low-code/no-code (LCNC) ML solution for handling real-world, enterprise use cases. Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data.

ML 124
article thumbnail

How OLAP and AI can enable better business

IBM Journey to AI blog

Here’s an overview of the key characteristics: AI-powered analytics : Integration of AI and machine learning capabilities into OLAP engines will enable real-time insights, predictive analytics and anomaly detection, providing businesses with actionable insights to drive informed decisions.

article thumbnail

Introducing the Topic Tracks for ODSC East 2024?—?Highlighting Gen AI, LLMs, and Responsible AI

ODSC - Open Data Science

This track will focus on helping you build skills in text mining, data storytelling, data mining, and predictive analytics through use cases highlighting the latest techniques and processes to collect, clean, and analyze growing volumes of structured data.