Remove Consulting Remove Data Enablement Remove Data Lake
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What is data architecture? A framework to manage data

CIO Business Intelligence

Data architecture goals The goal of data architecture is to translate business needs into data and system requirements, and to manage data and its flow through the enterprise. Many organizations today are looking to modernize their data architecture as a foundation to fully leverage AI and enable digital transformation.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

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DataOps For Business Analytics Teams

DataKitchen

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics. Is the team fully productive?

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps automation replaces the non-value-add work performed by the data team and the outside dollars spent on consultants with an automated framework that executes efficiently and at a high level of quality. The DataOps Platform does not replace a data lake or the data hub.

Analytics 246
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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

Data Lake 121
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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. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

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Periscope Data Expands to Israel, Empowering Data Teams with Powerful Tools

Sisense

Similarly, Kyle outlined how Flexport , the world’s first international freight forwarder and customs brokerage built around an online dashboard, uses Periscope Data to analyze billions of records, and get answers in seconds. Kongregate has been using Periscope Data since 2013. shone the spotlight on best practices with data lakes.