CIO Business Intelligence
APRIL 25, 2024
Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.
Jet Global
NOVEMBER 5, 2020
OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.
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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.
AWS Big Data
MARCH 7, 2023
Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.
AWS Big Data
APRIL 20, 2023
Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.
CIO Business Intelligence
APRIL 14, 2022
DaaS vendors can also improve the quality of data that an organization might otherwise gather itself by correcting errors or filling in gaps and even provide big blocks of data should you need more. In this way, DaaS providers can improve your homegrown data warehouse by cross-fertilizing it with other, curated sources.
Jet Global
OCTOBER 30, 2020
What are unstructured data? First, let’s consider what “structured” data looks like: CustomerID. Structured data are, by their very nature, orderly and predictable. Artificial intelligence is the solution to that problem, and that’s what data lakes are made to handle. CustomerName. Balance Due. XYZ Company.
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