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

CIO Business Intelligence

Enterprises must reimagine their data and document management to meet the increasing regulatory challenges emerging as part of the digitization era. The cost of compliance These challenges are already leading to higher costs and greater operational risk for enterprises. One particular challenge lies in managing “dark data” (i.e.,

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Or, as one of our customers put it, “How do I increase the total amount of team insight generated without continually adding more staff (and cost)?” Staff turnover, stress, and unhappiness. It’s not been going well.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications. Did you know?

Big Data 275
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How Encored Technologies built serverless event-driven data pipelines with AWS

AWS Big Data

Encored Technologies (Encored) is an energy IT company in Korea that helps their customers generate higher revenue and reduce operational costs in renewable energy industries by providing various AI-based solutions. It allows for efficient data storage and transmission, as well as easy manipulation of the data using specialized software.

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Introducing generative AI upgrades for Apache Spark in AWS Glue (preview)

AWS Big Data

Organizations run millions of Apache Spark applications each month on AWS, moving, processing, and preparing data for analytics and machine learning. Data practitioners need to upgrade to the latest Spark releases to benefit from performance improvements, new features, bug fixes, and security enhancements. Original code (Glue 2.0)

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246