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5 hot IT budget investments — and 2 going cold

CIO

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). This applies to his IT group as well, specifically, in using AI to automate the review of customer contracts, Nardecchia says.

Budget 363
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Data Virtualization Drives Volkswagen Pon Financial Services to Business Victory

TIBCO - Connected Intelligence

Today, it has grown into a top-class financial player in the automotive market, specializing in finance, leasing, insurance, and mobility. This growth has skyrocketed the company from a simple bank in the Netherlands to a global insurance leader. We can easily unlock data from multiple sources for any type of question.

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data 84
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The role of self-service BI for business agility

Capgemini

And they also need to trust that the data is current, relevant, and available. Moving a business forward requires fast access to good data for more applications. But that turns IT and analytics teams into the bottleneck. The goal should be to build a culture where people seek to understand data and its context.

Agile 52
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Process Mining Explained: Techniques, Applications, and Challenges

Altexsoft

Process mining is a set of techniques for the analysis of operational processes based on event logs extracted from company’s databases, information systems, or business management software such as enterprise resource planning (ERP), customer relationship management (CRM), electronic health records (EHR), etc. What is process mining?

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

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Procurement Analytics: Challenges, Opportunities, and Implementation Approaches

Altexsoft

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.