Business Intelligence Related Topics 
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.
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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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
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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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
TechCrunch
AUGUST 19, 2021
Open-source business intelligence company Metabase announced Thursday a $30 million Series B round led by Insight Partners. Due to Metabase often being someone’s first business intelligence tool, he is also doubling down on resources to help educate customers on how to ask questions and learn from their data.
CIO
JANUARY 20, 2023
Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions.
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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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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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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: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Our esteemed speakers will discuss the emerging trends shaping the future of product management and business intelligence.
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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.
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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