Octopai
JANUARY 21, 2020
How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. This is how the Online Analytical Processing (OLAP) cube was born, which you might call one of the grooviest BI inventions developed in the 70s.
Cloudera
DECEMBER 1, 2020
For example, a utility company using the operational database for OLTP use cases can use Cloudera’s operational database to store smart meter data and later use the data for OLAP use cases. For example, a finance organization that is using an operational database and OLTP for predicting credit-worthiness and lifetime customer value.
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Jet Global
DECEMBER 1, 2020
Finance teams often work with business intelligence (BI) tools to analyze data, identify trends, pinpoint discrepancies, and build informative, compelling reports for management. The good news is that an alternative exists that enables members of the finance team to set up and maintain a BI environment without all the hassle and expense.
Jet Global
SEPTEMBER 22, 2023
This metadata-driven approach also allows the project to be managed easily by multiple contributors and documentation to be generated on demand. Pre-built OLAP cubes, tabular models, and a data warehouse. Boost refresh times with star schemas, tabular models, and OLAP cubes. Turnkey installation in hours, not months.
Jet Global
MAY 1, 2023
OLAP cubes Used for multi-dimensional analysis Strategic Objective When a vendor-specific connector is not available, generic connectors provide flexibility with data. Metadata Self-service analysis is made easy with user-friendly naming conventions for tables and columns. Requirement ODBC/JDBC Used for connectivity. addresses).
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