Tableau
JUNE 6, 2022
Product Marketing Manager, Embedded Analytics, Tableau. Embedding analytics is a way we can help our customers make smarter decisions and achieve greater success. When creating an embedded analytics offering, the biggest decision is whether to build an in-house solution or purchase a turnkey solution.
Tableau
JUNE 6, 2022
Product Marketing Manager, Embedded Analytics, Tableau. Embedding analytics is a way we can help our customers make smarter decisions and achieve greater success. When creating an embedded analytics offering, the biggest decision is whether to build an in-house solution or purchase a turnkey solution. .
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Insight Software
JANUARY 17, 2022
The BI solutions you evaluate should be compatible with your current data environment, while at the same time have enough flexibility to meet future demands as your data architecture evolves. Also ask yourself if your users need to transform or enrich data for analysis. Embeddability and Customization.
Sisense
AUGUST 14, 2020
In the case of a stock trading AI, for example, product managers are now aware that the data required for the AI algorithm must include human emotion training data for sentiment analysis. It turns out that emotional reaction is an important variable in stock market behavior!
Sisense
FEBRUARY 10, 2021
This presented the first challenge for our product team in building Cascade Insight: What is the data that is most important to capture? However, defining the data requirements was important for understanding what data you need to measure to provide analytical insights.
Data Pine
NOVEMBER 27, 2019
Long-standing barriers between data scientists and business users are being slowly mixed into a one-stop-shop for any data requirement a company might have – from collecting, analyzing, monitoring and reporting on findings. Let’s now tackle the last of our BI and analytics trends 2020! 10) Embedded Analytics.
Sisense
SEPTEMBER 3, 2020
“The head of our content acquisition team, a major data consumer, was unsure about our switch. She was worried about transition costs and maintaining access to her particular data requirements.” Jennah says. All of these considerations will influence how quickly a new platform can be implemented.
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