Gartner Business Intelligence Summit – My Take
ElegantJ BI
JUNE 17, 2015
I attended the Gartner Business Intelligence, Analytics and Information Management Summit, 2015 , held in India on June 9 and 10 in Mumbai.
ElegantJ BI
JUNE 17, 2015
I attended the Gartner Business Intelligence, Analytics and Information Management Summit, 2015 , held in India on June 9 and 10 in Mumbai.
ElegantJ BI
JUNE 17, 2015
I attended the Gartner Business Intelligence, Analytics and Information Management Summit, 2015 , held in India on June 9 and 10 in Mumbai.
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ElegantJ BI
JUNE 17, 2015
I attended the Gartner Business Intelligence, Analytics and Information Management Summit, 2015 , held in India on June 9 and 10 in Mumbai. Navigating the Data Lake – Adam Ronthal. Big Data Discovery – Rita Sallam. Interactive Visualizations for Everyone – Rita Sallam.
The BAWorld
NOVEMBER 20, 2024
Here’s a brief comparison: Tableau: For data visualization specialists, Tableau is more preferred. QlikView: Provides powerful data discovery and analytics capabilities but is not as user-friendly as Power BI Looker: Mainly data exploration and, for companies already invested in Google’s ecosystem, makes even more sense.
Data Pine
SEPTEMBER 27, 2022
17) “SQL Database Programming” (2015 Edition) By Chris Fehily. You can also utilize data discovery tools to get additional insight into the importance of data and how to approach it. SQL Database Programming” could also have been listed as an SQL book for beginners. Viescas, Douglas J.
Data Pine
MAY 9, 2019
You can view business intelligence as an extremely powerful data discovery tool that is an extension of your fast thinking mind. They prevent you from drowning in data. The fact is, without business intelligence, you risk the very real possibility of drowning in data. quintillion bytes of data produced daily.
Data Pine
SEPTEMBER 4, 2023
By scrolling, clicking, and moving the cursor over interesting data points, designers engage users on a deeper level and enable them to be a participant rather than a viewer alone, adding more meaning to the data discovery learning process as a result. Back in 2015, when around 46.3
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