IBM Big Data Hub

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.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

Sisense

OCTOBER 6, 2020

Despite its many uses, quantitative data presents two main challenges for a data-driven organization. First, data isn’t created in a uniform, consistent format. It’s generated by a host of sources in different ways. Qualitative data benefits: Unlocking understanding.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Cloudera

AUGUST 31, 2020

Given the prohibitive cost of scaling it, in addition to the new business focus on data science and the need to leverage public cloud services to support future growth and capability roadmap, SMG decided to migrate from the legacy data warehouse to Cloudera’s solution using Hive LLAP. The case for a new Data Warehouse?

Slice and Dice 67

Slice and Dice Management Data Warehouse Analytics 67