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Data Teams and Their Types of Data Journeys

DataKitchen

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

Benefits of Healthcare Business Intelligence Tools Improved Decision-Making: Healthcare BI tools enable informed decision-making by providing real-time data analysis and predictive insights. In addition to security concerns, achieving seamless healthcare data integration and interoperability presents its own set of challenges.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

This is underpinned by building a complete patient profile that enables claim analysts to identify patterns, trends, potential gaps in care, and adherence to care plans. The solution proposed in this post follows a zero-ETL approach to data integration to facilitate near real-time analytics and deliver a more personalized patient experience.

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Data-driven competitive advantage in the financial services industry

Cloudera

Cloudera’s customers in the financial services industry have realized greater business efficiencies and positive outcomes as they harness the value of their data to achieve growth across their organizations. Data enables better informed critical decisions, such as what new markets to expand in and how to do so.

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Process and analyze highly nested and large XML files using AWS Glue and Amazon Athena

AWS Big Data

Analyzing XML files can also help in data integration, because many applications and systems use XML as a standard data format. With these techniques, you can enhance the processing speed and accessibility of your XML data, enabling you to derive valuable insights with ease. xml and technique2.xml.

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How to choose the best AI platform

IBM Big Data Hub

Gaining an understanding of available AI tools and their capabilities can assist you in making informed decisions when selecting a platform that aligns with your business objectives. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

AWS Secrets Manager is an AWS service that can be used to store sensitive data, enabling users to keep data such as database credentials out of source code. Business results The data lake implementation in Ruparupa took around 3 months, with an additional month for data validation, before it was considered ready for production.