Business Intelligence Data Silos Data Warehouse 
IBM Journey to AI blog
FEBRUARY 2, 2023
In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.
Pickl AI
NOVEMBER 15, 2023
Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
IBM Journey to AI blog
OCTOBER 22, 2024
The data universe is expected to grow exponentially with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase pressure to manage cloud costs efficiently and complicate governance of AI and data workloads.
Alation
MARCH 29, 2022
Business intelligence has a long history. Today, the term describes that same activity, but on a much larger scale, as organizations race to collect, analyze, and act on data first. With remote and hybrid work on the rise, the ability to locate and leverage data and expertise — wherever it resides — is more critical than ever.
IBM Journey to AI blog
MAY 9, 2023
Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]
AWS Machine Learning Blog
DECEMBER 29, 2022
Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.
Dataconomy
APRIL 27, 2023
Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.
Expert insights. Personalized for you.
58 
Let's personalize your content