Remove Data Enablement Remove Metadata Remove Risk
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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

It addresses many of the shortcomings of traditional data lakes by providing features such as ACID transactions, schema evolution, row-level updates and deletes, and time travel. In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient.

Metadata 118
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A Data Prediction for 2025

DataKitchen

The crazy idea is that data teams are beyond the boom decade of “spending extravagance” and need to focus on doing more with less. This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. ’ They are data enabling vs. value delivery.

Metadata 130
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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. The Right Tools.

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Why Is Data Loss Prevention is Crucial for Business?

Smart Data Collective

A comprehensive DLP plan can monitor data in transit within networks, cloud storage, and active endpoints. In addition to vulnerability assessment, DLP improves system administrators’ visibility – they can track how every user accesses data and bring the risk of a data leak to a minimum. Building a DLP Plan.

Risk 139
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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Leveraging data where it lies.

Analytics 111
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Best Practices for Data Catalog Implementation

Octopai

For business users Data Catalogs offer a number of benefits such as better decision-making; data catalogs provide business users with quick and easy access to high-quality data. This availability of accurate and timely data enables business users to make informed decisions, improving overall business strategies.

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How AI-driven data management helps organizations meet rising regulatory challenges

CIO Business Intelligence

With data volumes and AI deployments set to grow, as well as new regulatory requirements in areas such as sustainability, it’s clear this must be a high priority for technology leaders. The cost of compliance These challenges are already leading to higher costs and greater operational risk for enterprises. Data classification.