... Growing data volumes and wide distribution at scale are making it hard for organizations to exploit their data assets efficiently and effectively. Data and analytics leaders need to adopt a semantic approach to their enterprise data to drive business value and break data silos, especially for cases using ...
Analyst(s): Robert Thanaraj | Roxane Edjlali | Guido De Simoni
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... Data and analytics leaders often seek Gartner’s guidance on managing their engagement with Palantir toward their desired business outcomes. Use this research to understand Palantir’s delivery model, and thereby plan and carry out your Palantir engagement successfully. More Detail Gartner Recommended ...
Analyst(s): Mark Beyer | Rita Sallam | Ehtisham Zaidi | Robert Thanaraj
... Organizations must have a robust strategy for provisioning the data for development, training, testing, deploying and monitoring of machine learning (ML) models. This document guides data scientists on how to build an effective technical data strategy for data to deliver ML initiatives. Overview Problem Statement ...
... especially those introduced by GenAI, make business-driven data security challenging. This research offers security and risk management leaders ways to build a multidisciplinary program with business-centric processes to secure on-premises and cloud data. Strategic Planning Assumptions Analysis Research Highlights ...
... a Gartner client? Unchecked data growth is significantly inflating enterprise cloud and SaaS storage costs. By embedding archive-first data volume controls upstream in budget and renewal cycles, heads of I&O can stop inactive data growth before it is committed, reduce data costs, and redirect capacity ...
Analyst(s): Rizvan Hussain | Michael Hoeck | Apurva Singh
... Data and analytics leaders need to support the opportunities and challenges of today’s digital business with the right competencies. Now is the time to create data and analytics roles that are fit for the future. Strategic Planning Assumption(s) Analysis Research Highlights Gartner Insights Abstract ...
Analyst(s): Alan D. Duncan | Saul Judah | Jorgen Heizenberg
... I&O and data leaders struggle to distinguish between observability and data observability, risking operational failures and misaligned investments. Understanding the difference and commonalities ensures the right tools are used to maintain system resilience and data integrity and trustworthiness. More ...
... Packaging data quality is a growing risk for organizations as legislation requires reporting, accuracy, and accountability. The vendors highlighted in this research are transforming the market with innovative AI and data expertise, enabling supply chain technology leaders to address data quality. Overview ...
... Migrating data to a new cloud ERP system capable of supporting composability is a crucial process demanding careful preparation, planning and extensive data governance. ERP leaders can use the three steps and best practices in this research to prepare for the data migration process. Overview Introduction ...