erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Jet Global

APRIL 20, 2020

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Today’s technology takes this evolution a step further.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

erwin

AUGUST 15, 2022

I was pricing for a data warehousing project with just 4 TBs of data, small by today’s standards. I chose “ON Demand” for up to 64 virtual CPUs and 448 GB of memory since I wanted this data warehouse to fit entirely, or at least mostly, within memory. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Jet Global

MAY 6, 2022

Their combined utility makes it easy to create and maintain a complete data warehouse solution with very little effort. Jet acts as the perfect conduit between your ERP data and Power BI. Jet Analytics provides data warehouse automation for fast, consistent business analytics and master data management.

Data Warehouse 52

Data Warehouse Visualization Finance Reporting 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more. Use in-depth show-and-tell.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52