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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO

Some are relying on outmoded legacy hardware systems. Most have been so drawn to the excitement of AI software tools that they missed out on selecting the right hardware. 2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security.

Analytics 205
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Sightfull, a startup that tracks key business activities, raises $18M

TechCrunch

“[We aim to bridge] revenue analytics and business intelligence by using automation that enables software-as-a-service (SaaS) companies to leverage the full power of their business data,” Liran added. Currently, Sightfull has roughly a dozen SaaS customers, including Wiz and storage hardware startup VAST Data.

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The Good and The Bad of SAP Business Intelligence Platform

Altexsoft

In the business sphere, a certain area of technology aims at helping people make the right decisions, by supporting them with the right data. This field is called business intelligence or BI. Business intelligence includes multiple hardware and software units that serve the same idea: take data and show it to the right people.

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Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools

Altexsoft

The answer is business intelligence. In this article, we will discuss the actual steps of bringing business intelligence into your existing corporate infrastructure. You will learn how to set up a business intelligence strategy and integrate tools into your company workflow. What is business intelligence?

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Building a Beautiful Data Lakehouse

CIO

As such, the lakehouse is emerging as the only data architecture that supports business intelligence (BI), SQL analytics, real-time data applications, data science, AI, and machine learning (ML) all in a single converged platform. Challenges of supporting multiple repository types. Pulling it all together.

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Edge Delta raises $15M Series A to take on Splunk

TechCrunch

He acknowledges that traditional big data warehousing works quite well for business intelligence and analytics use cases. It worked 10 years ago, but gigabytes turned into terabytes and now terabytes are turning into petabytes. That whole model is breaking down.” ” Image Credits: Edge Delta.

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How to build analytic products in an age when data privacy has become critical

O'Reilly Media - Data

Business intelligence and analytics. There are already systems for doing BI on sensitive data using hardware enclaves , and there are some initial systems that let you query or work with encrypted data (a friend recently showed me HElib , an open source, fast implementation of homomorphic encryption ).

Analytics 186