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Achieving Business Analytics Success

Datavail

Analytics as an Operational Tool. Despite their promise as a business building engine, and even with significant investments in the science, research reveals that over 85% of data implementation projects fail to achieve their goals. The post Achieving Business Analytics Success appeared first on Datavail.

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What is data analytics? Analyzing and managing data for decisions

CIO

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics vs. business analytics.

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Ascend.io lands $31M to automate data pipeline orchestration

TechCrunch

Ascend.io , a company developing data automation products for enterprise customers, has raised $31 million in a Series B round led by Tiger Global with participation from Shasta Ventures and existing investor Accel, it announced today. There’s no denying that the pandemic bolstered the adoption of AI and analytics technologies.

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What Do CIOs Have To Know About Business Intelligence?

The Accidental Successful CIO

Understanding Business Intelligence vs. Business Analytics. Business intelligence tools provide insights into the current state of the business or organization: where are sales prospects in the pipeline today? It also gets to the heart of the question of who business intelligence is designed for.

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Don’t Blink: You’ll Miss Something Amazing!

Cloudera

And all of this should ideally be delivered in an easy to deploy and administer data platform available to work in any cloud. Making sure data is able to land in real time and be accessed just as fast requires a “best fit” partitioning scheme. Kudu has this covered.

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Forget the Rules, Listen to the Data

Hu's Place - HitachiVantara

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

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ChatGPT: le nuove sfide della strategia sui dati nell’era dell’IA generativa

CIO

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

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