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5 modern challenges in data integration and how CIOs can overcome them

CIO Business Intelligence

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. Heterogeneous sources produce data sets of different formats and structures.

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Optimize SAP Data Analysis for a Sustainable Future

Jet Global

Improper load optimization: Often caused by inefficient planning and inadequate utilization of cargo space, leading to poor transportation efficiency such as half-full containers. Optimize for a greener future: Leverage insights to implement resource-saving technologies, optimize logistics, and source from sustainable suppliers.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

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Announcing zero-ETL integrations with AWS Databases and Amazon Redshift

AWS Big Data

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

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How AWS helped Altron Group accelerate their vision for optimized customer engagement

AWS Big Data

He has been leading the building of data warehouses and analytic solutions for the past 20 years. The Altron team created an AWS Glue crawler and configured it to run against Azure SQL to discover its tables.