Jet Global
OCTOBER 26, 2021
Multi-dimensional analysis is sometimes referred to as “OLAP”, which stands for “online analytical processing.” Technically speaking, OLAP refers to methodologies for producing multidimensional analysis on high-volume data sets.). For excellence in both reporting and analytics, invest in the right tools.
AWS Big Data
MARCH 7, 2023
Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.
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Jet Global
AUGUST 14, 2019
The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
AWS Big Data
JUNE 21, 2023
Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. For setup instructions, refer to AWS security credentials. In AWS Glue Studio, create a job and select Visual with a blank canvas. Choose Amazon DynamoDB as the data source.
Sisense
AUGUST 11, 2019
BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. Business Analytics is One Part of Business Intelligence.
Jet Global
OCTOBER 2, 2019
The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.
Jet Global
SEPTEMBER 4, 2020
Microsoft referred to this approach as “bring your own database” (BYOD). Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. Jet Analytics provides enterprise-grade capabilities at a predictable cost.
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