Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. 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.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Jet Global

OCTOBER 2, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

IBM Big Data Hub

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

OLAP 60

OLAP Slice and Dice Cost-Benefit Data Warehouse 60

Sisense

FEBRUARY 16, 2021

Data warehouses have become intensely important in the modern business world. For many organizations, it’s not uncommon for all their data to be extracted, loaded unchanged into data warehouses, and then transformed via cleaning, merging, aggregation, etc. OLTP does not hold historical data, only current data.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

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.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

Jet Global

JUNE 5, 2019

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Jet Global

OCTOBER 22, 2020

Most organizations are looking for sophisticated reporting and analytics, but they have little appetite for managing the highly complicated infrastructure that goes with it. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 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. Making Sense of Disparate Systems.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

IBM Big Data Hub

SEPTEMBER 25, 2023

To address their performance needs, Uber chose Presto because of its ability, as a distributed platform, to scale in linear fashion and because of its commitment to ANSI-SQL, the lingua franca of analytical processing. Uber chose Presto for the flexibility it provides with compute separated from data storage.

OLAP 90

OLAP Data Lake Data-driven Snapshot 90