IBM Big Data Hub
APRIL 25, 2023
To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.
AWS Big Data
FEBRUARY 29, 2024
Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail.
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CDW Research Hub
APRIL 20, 2020
Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications.
CIO Business Intelligence
FEBRUARY 16, 2023
Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.
IBM Big Data Hub
SEPTEMBER 19, 2023
Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.
AWS Big Data
JULY 31, 2023
This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution.
AWS Big Data
MARCH 26, 2024
A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.
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