Business Intelligence Related Topics 
CIO
OCTOBER 26, 2023
Business intelligence (BI) analysts transform data into insights that drive business value. What does a business intelligence analyst do? The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies.
TechCrunch
DECEMBER 14, 2023
In recent years, there has been a proliferation of business intelligence tools that aim to help companies make critical business decisions based on data analytics. There’s a catch. “The sprawl that inevitably comes […] © 2023 TechCrunch.
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TechCrunch
NOVEMBER 14, 2022
Zenlytic, a business intelligence tool for commerce, secured $5.4 As my colleague Kyle Wiggers wrote earlier this year , business intelligence is getting some love from venture capital firms as the category yields more solutions for managing and analyzing large amounts of data so customers can identify new revenue opportunities.
TechCrunch
MARCH 19, 2021
Organizations spend ungodly amounts of money — millions of dollars — on business intelligence (BI) tools. Because BI has failed businesses. He has more than 20 years’ experience in the analytics market, including 10+ years of direct customer implementation experience. Yet, adoption rates are still below 30%.
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Dresner Advisory Services has just unveiled their “2022 Business Intelligence Market Study,” an in-depth look at the business intelligence industry that ranks more than two dozen BI vendors in areas like product, service, support, and overall customer satisfaction. Who’s the perfect vendor for your business needs?
TechCrunch
OCTOBER 28, 2020
We’ve seen our fair share of business intelligence (BI) platforms that aim to make data analysis accessible to everybody in a company. “I have seen the business intelligence problems in the past,” Panuganty said. Most of them are still fairly complicated, no matter what their marketing copy says.
CIO
AUGUST 11, 2021
Business intelligence is not an oxymoron like jumbo shrimp. And it’s not being superseded by artificial intelligence. It’s not dead. To read this article in full, please click here (Insider Story)
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
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Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them. Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps.
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities?
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In its 2020 Embedded BI Market Study, Dresner Advisory Services continues to identify the importance of embedded analytics in technologies and initiatives strategic to business intelligence. Discover the top seven requirements to consider when evaluating your embedded dashboards and reports.
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We interviewed 16 experts across business intelligence, UI/UX, security and more to find out what it takes to build an application with analytics at its core. Embedding dashboards, reports and analytics in your application presents unique opportunities and poses unique challenges.
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You’ll learn: The evolution of business intelligence. How do you differentiate one solution from the next? Choosing the best solution for your dashboards and reports starts with understanding the types of analytics solutions on the market. 4 common approaches to analytics for your application. The pros and cons for each option.
Speaker: Sriram Parthasarathy
How predictive analytics and business intelligence can be used together to drive smarter business decisions. We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value. Why every application that fails to talk about the future is at risk of getting replaced.
Speaker: Kate Owens and Megan Bubley, SpotHero, Diana Smith, Segment, and Erin Franz, Looker
Plus, hear from SpotHero’s Product Manager and Business Intelligence Lead, Megan Bubley and Kate Owens, as they describe how they not only unified their siloed data but aligned their team on what it all means. As your sources of data increase, so do the complexities of unifying the data in a meaningful way.
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