Remove Cost-Benefit Remove Data Processing Remove Optimization Remove Unstructured Data
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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.

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An Introduction To Data Dashboards: Meaning, Definition & Industry Examples

datapine

Without the existence of dashboards and dashboard reporting practices, businesses would need to sift through colossal stacks of unstructured data, which is both inefficient and time-consuming. With such dashboards, users can also customize settings, functionality, and KPIs to optimize their dashboards to suit their specific needs.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. However, a more detailed analysis is needed to make an informed decision.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

This is partly because integrating and moving data is not the only problem. The data itself is stored in a way that is not optimal for extracting insight. Unlocking additional value from data requires context, relationships, and structure, none of which are present in the way most organizations store their data today.

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

Sumit started his talk by laying out the problems in today’s data landscapes. One of the major challenges, he pointed out, was costly and inefficient data integration projects. Lance introduced himself as an ”engineer who avoided databases at all cost before discovering SPARQL”.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Ontotext Invents the Universe So You Don’t Need To

Ontotext

The ability to define the concepts and their relationships that are important to an organization in a way that is understandable to a computer has immense benefits. Data and content are organized in a way that facilitates discoverability, insights and decision making rather than be bound by limitations of data formats and legacy systems.