2022 Data Architecture Data Warehouse Reporting 
CIO Business Intelligence
OCTOBER 13, 2023
They often report to data infrastructure and data science leads. Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects.
AWS Big Data
MAY 17, 2023
million at the end of 2022. As Peloton’s business continued to evolve amid a changing macroeconomic environment, it was essential that it could make smart business decisions quickly, and one of the best ways to do that was to harness insights from the huge amount of data that it had been gathering over recent years.
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Cloudera
JULY 11, 2022
What used to be bespoke and complex enterprise data integration has evolved into a modern data architecture that orchestrates all the disparate data sources intelligently and securely, even in a self-service manner: a data fabric. Cloudera data fabric and analyst acclaim. Next steps.
AWS Big Data
APRIL 19, 2023
Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.
CIO Business Intelligence
SEPTEMBER 21, 2023
In a recent report, he estimated that gen AI software revenues will grow from $3.7 He’s currently tracking 262 gen AI vendors, of which 117 specialize in text generation, and plans to produce a new version of the report in the next six months. billion this year to $36 billion by 2028. Then gen AI came out.
Alation
APRIL 25, 2023
Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029. And the rise in data valuation has been compared to that of oil during the 19th century. The comparison makes sense because, like petroleum, data has enormous potential. This is where a reverse ETL process is needed.
CIO Business Intelligence
APRIL 4, 2023
In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.
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